commit 8eec9e65b22c69292469a398873dd973ad2c25df
Author: Alexander Nozik <altavir@gmail.com>
Date:   Sat Sep 24 11:25:54 2022 +0300

    Initial commit

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+.idea/
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+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "# PART I: NumPy."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "# Programming in python"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "source": [
+    "## Writing code\n",
+    "\n",
+    "* code should be readable\n",
+    "\n",
+    "* style guides\n",
+    "    * PEP8 (PEP = Python Enhancement Proposal) http://legacy.python.org/dev/peps/pep-0008/\n",
+    "    * writing idiomatic code https://david.goodger.org/projects/pycon/2007/idiomatic/handout.html ('idiomatic' means 'conforming to the natural mode of expression in a given context')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "source": [
+    "## Avoiding worst practices\n",
+    "http://docs.quantifiedcode.com/python-anti-patterns/"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "# NumPy: beginner's references\n",
+    "\n",
+    "* From Python to NumPy\n",
+    "https://www.labri.fr/perso/nrougier/from-python-to-numpy/\n",
+    "    \n",
+    "* 100 NumPy Exercises\n",
+    "https://github.com/rougier/numpy-100/blob/master/100_Numpy_exercises.md"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "# NumPy"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "source": [
+    "## Constructing matrices and vectors "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "A = \n",
+      "[[3 3 0]\n",
+      " [2 1 1]\n",
+      " [1 1 0]\n",
+      " [3 0 2]]\n",
+      "\n",
+      " b = \n",
+      "[3 2 0]\n"
+     ]
+    }
+   ],
+   "source": [
+    "import numpy as np\n",
+    "\n",
+    "A = np.array([[3, 3, 0],\n",
+    "              [2, 1, 1],\n",
+    "              [1, 1, 0],\n",
+    "              [3, 0, 2]])\n",
+    "\n",
+    "b = np.array([3, 2, 0])\n",
+    "\n",
+    "print(f'A = \\n{A}\\n\\n b = \\n{b}')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "source": [
+    "## Initializers "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {
+    "scrolled": true,
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[0. 0. 0.]\n",
+      "[1. 1. 1.]\n",
+      "[[1. 0. 0.]\n",
+      " [0. 1. 0.]\n",
+      " [0. 0. 1.]]\n",
+      "[0 1 2]\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(np.zeros(3))\n",
+    "print(np.ones(3))\n",
+    "print(np.eye(3))\n",
+    "print(np.arange(3))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "## Use numpy arrays, not lists"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "4.75 µs ± 348 ns per loop (mean ± std. dev. of 7 runs, 100 loops each)\n",
+      "173 µs ± 3.06 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n"
+     ]
+    }
+   ],
+   "source": [
+    "n = 10000\n",
+    "%timeit -n 100 np.ones(n)\n",
+    "%timeit -n 100 [1 for i in range(n)]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "## Basic operations "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([15,  8,  5,  9])"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# matrix-vector multiplication: .dot()\n",
+    "A.dot(b)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([15,  8,  5,  9])"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# same as\n",
+    "A @ b"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "## Broadcasting\n",
+    "https://numpy.org/doc/stable/user/basics.broadcasting.html"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "source": [
+    "Broadcasting is very important for writing concise and efficient code. "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "## Data types"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "dtype('float32')"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "vector32 = np.array([1.2, 3.2, 4.9, 1.8], dtype=np.single)\n",
+    "vector32.dtype"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "dtype('float64')"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "vector64 = np.array([1.2, 3.2, 4.9, 1.8], dtype=np.double)\n",
+    "vector64.dtype"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "source": [
+    "Double-precision calculations are usually MUCH slower on GPU. On CPU, float32 is a bit faster than float64 can be preferred for memory reasons. Normally, you should use single for machine learning applications and  double for scientific computations (especially for not-so-well conditioned problems)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "404 µs ± 5.89 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n"
+     ]
+    }
+   ],
+   "source": [
+    "b = np.random.normal(size=(1000, 1000)).astype(np.float32)\n",
+    "%timeit -n 100 np.sum(b**2)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "927 µs ± 7.27 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n"
+     ]
+    }
+   ],
+   "source": [
+    "b = np.random.normal(size=(1000, 1000)).astype(np.float64)\n",
+    "%timeit -n 100 np.sum(b**2)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "## Shapes"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "vector [[1 2 3]] has dimensionality (1, 3)\n"
+     ]
+    }
+   ],
+   "source": [
+    "b = np.array([[1,2,3]])\n",
+    "print(f'vector {b} has dimensionality {b.shape}')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[1 2 3]\n",
+      "(3,)\n"
+     ]
+    }
+   ],
+   "source": [
+    "# remove axis of length 1\n",
+    "b = b.squeeze()\n",
+    "print(b)\n",
+    "print(b.shape)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "## More on broadcasting"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([[1, 2, 3],\n",
+       "       [2, 3, 4],\n",
+       "       [3, 4, 5]])"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "A = np.array([[1,2,3],[2,3,4],[3,4,5]])\n",
+    "A"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([1, 2, 3])"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "b"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([[ 1,  4,  9],\n",
+       "       [ 2,  6, 12],\n",
+       "       [ 3,  8, 15]])"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# multiply matrix by a vector row-wise  \n",
+    "A*b"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([[ 1,  4,  9],\n",
+       "       [ 2,  6, 12],\n",
+       "       [ 3,  8, 15]])"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# this is the same, of course\n",
+    "b*A"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([[ 1,  2,  3],\n",
+       "       [ 4,  6,  8],\n",
+       "       [ 9, 12, 15]])"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# multiply matrix by a vector row-wise \n",
+    "A*b[:,None]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "## Indexing (slicing) vectors "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([0, 1, 2, 3, 4, 5])"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "b = np.arange(6)\n",
+    "b"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "source": [
+    "What is the output?"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[0 1 2]\n",
+      "5\n",
+      "[0 1 2 3]\n",
+      "[2 3]\n",
+      "[0 2 4]\n",
+      "[5 3 1]\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(b[:3])\n",
+    "print(b[-1])\n",
+    "print(b[:-2])\n",
+    "print(b[2:4])\n",
+    "print(b[::2])\n",
+    "print(b[::-2])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "## Indexing (slicing) matrices"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {
+    "scrolled": true,
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([[0, 1, 2],\n",
+       "       [3, 4, 5]])"
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "A = b.reshape(2, 3)\n",
+    "A"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "source": [
+    "What is the output?"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([[0, 1, 2],\n",
+       "       [3, 4, 5]])"
+      ]
+     },
+     "execution_count": 20,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "A"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[0 3]\n",
+      "[3 4 5]\n",
+      "[[0 2]\n",
+      " [3 5]]\n",
+      "[[0 1]\n",
+      " [3 4]]\n",
+      "[]\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(A[:, 0])\n",
+    "print(A[-1, :])\n",
+    "print(A[:,::2])\n",
+    "print(A[:3, :-1])\n",
+    "print(A[3:, 1])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([[0, 1, 2],\n",
+       "       [3, 4, 5]])"
+      ]
+     },
+     "execution_count": 22,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "A"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([[0, 1],\n",
+       "       [3, 4]])"
+      ]
+     },
+     "execution_count": 23,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "A[:2, :2]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "## View vs Copy"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([[1, 2, 3],\n",
+       "       [2, 3, 4],\n",
+       "       [3, 4, 5]])"
+      ]
+     },
+     "execution_count": 24,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "A = np.array([[1,2,3],[2,3,4],[3,4,5]])\n",
+    "A"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([1, 2, 3])"
+      ]
+     },
+     "execution_count": 25,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "sub_A = A[:,0]\n",
+    "sub_A"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([[1, 2, 3],\n",
+       "       [1, 3, 4],\n",
+       "       [1, 4, 5]])"
+      ]
+     },
+     "execution_count": 26,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "A[:,0] = 1\n",
+    "A"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([1, 1, 1])"
+      ]
+     },
+     "execution_count": 27,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "sub_A"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "# copies have to be created explicitly\n",
+    "A_copy = A.copy()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "# More benchmarks"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "## Computing convolutions: einsum"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "n = 100\n",
+    "a = np.random.normal(size=(n, n))\n",
+    "b = np.random.normal(size=(n, n))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "source": [
+    "Consider computation of $\\sum_{ij}a_{ij}b_{ji}$"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "The slowest run took 10.02 times longer than the fastest. This could mean that an intermediate result is being cached.\n",
+      "62.8 µs ± 86.4 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n"
+     ]
+    }
+   ],
+   "source": [
+    "%timeit -n 100 np.trace(np.dot(a, b))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "17.9 µs ± 7.12 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n"
+     ]
+    }
+   ],
+   "source": [
+    "%timeit -n 100 np.einsum('ij,ji->', a, b)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "source": [
+    "Tensor convolutions can be very tricky and may admit real optimizations. Trivial example:\n",
+    "$$\n",
+    "\\sum_{ijkl}A_{ij}B_{ji}B_{kl}A_{lk}\n",
+    "$$\n",
+    "How many FLOPs does it take to compute this sum?"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "## Memory access and performance"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "a = np.zeros(shape= 64 * 1024 * 1024, dtype=np.int64)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "source": [
+    "Which of the assignments should run faster?"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "37.2 ms ± 376 µs per loop (mean ± std. dev. of 7 runs, 1 loop each)\n"
+     ]
+    }
+   ],
+   "source": [
+    "%timeit a[::1] += 2"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "37.2 ms ± 29 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n"
+     ]
+    }
+   ],
+   "source": [
+    "%timeit a[::8] += 2"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "from timeit import timeit\n",
+    "def t(k):\n",
+    "    return timeit(f'a[::{k}]+=2', setup='import numpy as np; a = np.zeros(shape=64 * 1024 * 1024, dtype=np.int64)', number=32)/32"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "ks = 2**np.arange(10)\n",
+    "ts = [t(k) for k in ks]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import matplotlib.pyplot as plt\n",
+    "plt.plot(ks, ts)\n",
+    "plt.xscale('log')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "source": [
+    "Modern CPUs do not access memory byte by byte. Instead, they fetch memory in chunks of (typically) 64 bytes, called cache lines. When you read a particular memory location, the entire cache line is fetched from the main memory into the cache. And, accessing other values from the same cache line is cheap!\n",
+    "\n",
+    "Since 16 ints take up 64 bytes (one cache line), for-loops with a step between 1 and 16 have to touch the same number of cache lines: all of the cache lines in the array. But once the step is 32, we’ll only touch roughly every other cache line, and once it is 64, only every fourth."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "source": [
+    "More: http://igoro.com/archive/gallery-of-processor-cache-effects/"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "## More performance tips"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "source": [
+    "https://shihchinw.github.io/2019/03/performance-tips-of-numpy-ndarray.html"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "## JIT"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "source": [
+    "JIT = Just-In-Time compilation"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "def matmul(a, b):\n",
+    "    n = a.shape[0]\n",
+    "    k = a.shape[1]\n",
+    "    m = b.shape[1]  \n",
+    "    c = np.zeros((n, m))\n",
+    "    for i in range(n):\n",
+    "        for j in range(m):\n",
+    "            for s in range(k):\n",
+    "                c[i, j] += a[i, s] * b[s, j]\n",
+    "                \n",
+    "    return c"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 39,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "from numba import jit\n",
+    "\n",
+    "@jit(nopython=True)\n",
+    "def numba_matmul(a, b):\n",
+    "    n = a.shape[0]\n",
+    "    k = a.shape[1]\n",
+    "    m = b.shape[1]\n",
+    "    c = np.zeros((n, m))\n",
+    "    for i in range(n):\n",
+    "        for j in range(m):\n",
+    "            for s in range(k):\n",
+    "                c[i, j] += a[i, s] * b[s, j]\n",
+    "    return c"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "Let us compare computational times."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 40,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "392 ms ± 33.4 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n",
+      "The slowest run took 162.76 times longer than the fastest. This could mean that an intermediate result is being cached.\n",
+      "23.4 ms ± 55 ms per loop (mean ± std. dev. of 7 runs, 2 loops each)\n",
+      "59.4 µs ± 19.2 µs per loop (mean ± std. dev. of 7 runs, 4 loops each)\n"
+     ]
+    }
+   ],
+   "source": [
+    "n = 100\n",
+    "a = np.random.randn(n, n)\n",
+    "b = np.random.randn(n, n)\n",
+    "\n",
+    "%timeit -n 1 matmul(a, b)\n",
+    "%timeit -n 2 numba_matmul(a, b)\n",
+    "%timeit -n 4 np.dot(a, b)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "## Enter JAX"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "source": [
+    "JAX $\\approx$ Just After eXecution"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 41,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "import jax.numpy as jnp\n",
+    "import numpy as np"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 42,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "size = (1000, 1000)\n",
+    "a = np.random.normal(size=size)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 43,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "17.5 ms ± 61 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n"
+     ]
+    }
+   ],
+   "source": [
+    "%timeit -n 10 np.sum(a**3)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 44,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "1.55 ms ± 120 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n"
+     ]
+    }
+   ],
+   "source": [
+    "%timeit -n 10 np.sum(a*a*a)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 45,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "WARNING:absl:No GPU/TPU found, falling back to CPU. (Set TF_CPP_MIN_LOG_LEVEL=0 and rerun for more info.)\n"
+     ]
+    }
+   ],
+   "source": [
+    "a = jnp.asarray(a)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 46,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "544 µs ± 5.9 µs per loop (mean ± std. dev. of 7 runs, 1,000 loops each)\n"
+     ]
+    }
+   ],
+   "source": [
+    "%timeit jnp.sum(a**3).block_until_ready()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "source": [
+    "Simply replacing numpy with jax.numpy, we got a 20x speed-up. \n",
+    "jax.numpy can be even faster than pure C code due to very clever optimizations. We will discuss jax in more details in Lecture 7.\n",
+    "Meanwhile: https://github.com/google/jax/discussions/11078"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "# Part II: Vector and matrix norms. Orthogonal matrices."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "# Vector and matrix norms. Orthonogal matrices. "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "source": [
+    "## Reading\n",
+    "- Trefethen NLA, Lectures 1 - 3\n",
+    "- Tyrtyshnikov, Lecture 1"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "## Notations\n",
+    "\n",
+    "We use notation (for matrix of $m$ rows and $n$ columns) \n",
+    "\n",
+    "$$A= \\begin{bmatrix} a_{11} & \\dots & a_{1n} \\\\ \\vdots & \\ddots & \\vdots \\\\ a_{m1} & \\dots & a_{mn}  \\end{bmatrix}.$$"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "## Matrix-vector multiplication "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "source": [
+    "Let matrix $A$ be composed from columns $a_i$: $A = \\bigg[a_1\\bigg|a_2\\bigg|...\\bigg|a_n\\bigg]$ \n",
+    "\n",
+    "Then matrix-vector multiplication can be understood as follows:\n",
+    "$$\n",
+    "Ax = \\bigg[a_1\\bigg|a_2\\bigg|...\\bigg|a_n\\bigg]x = x_1 \\bigg[a_1\\bigg] + x_2 \\bigg[a_2\\bigg] + ... + x_n \\bigg[a_n\\bigg],\n",
+    "$$\n",
+    "that is column vector $b=Ax$ is a linear combination of columns of $A$."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "source": [
+    "## Matrix-vector multiplication: complexity\n",
+    "\n",
+    "Multiplication of an $n\\times n$ matrix $A$ by a vector $x$ of size $n\\times 1$ ($y=Ax$):\n",
+    "\n",
+    "$$\n",
+    "y_{i} = \\sum_{i=1}^n a_{ij} x_j\n",
+    "$$\n",
+    "\n",
+    "requires $n^2$ mutliplications and $n(n-1)$ additions. Thus, the overall complexity is $\\mathcal{O}(n^2)$ "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "source": [
+    "## Matrix-matrix product\n",
+    "A product of an $n \\times k$ matrix $A$ and a $k \\times m$ matrix $B$ is a $n \\times m$ matrix $C$ with the elements  \n",
+    "$$\n",
+    "   c_{ij} = \\sum_{s=1}^k a_{is} b_{sj}, \\quad i = 1, \\ldots, n, \\quad j = 1, \\ldots, m \n",
+    "$$\n",
+    "For $m=k=n$ complexity of a naive algorithm is $\\mathcal{O}(n^3)$. \n",
+    "\n",
+    "The rather elementary https://en.wikipedia.org/wiki/Strassen_algorithm allows to achieve $\\approx O(N^{2.81})$. Theoretically even faster algorithms (the best is $\\mathcal{O}(n^{2.37})$) exist, see a popular article https://www.quantamagazine.org/mathematicians-inch-closer-to-matrix-multiplication-goal-20210323/\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "## Range and nullspace "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "source": [
+    "- range(A) is the set of vectors, which can be expressed as $Ax$\n",
+    "- range(A) is the space spanned by the columns of $A$\n",
+    "- null(A) is the set of $x$ such that $Ax=0$"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "## Column and row rank "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "source": [
+    "- column rank is dimension of the column space\n",
+    "- row rank is dimension of the row space\n",
+    "- column rank is always equal to row rank"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "## Full rank matrix and inverse"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "source": [
+    "- The highest rank for a $m\\times n$ matrix is $\\min(m, n)$\n",
+    "- The $m\\times n$ matrix of a rank $\\min(m, n)$ is called full rank matrix\n",
+    "- Square $m\\times m$ matrix of a full rank is called non-singular matrix\n",
+    "- Non-singular matrix has an inverse $A^{-1}$ such that $A A^{-1} = A^{-1} A = 1$"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "source": [
+    "## Inverse matrix times a vector "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "source": [
+    "Geometric interpretation: Consider $x=A^{-1}b$. Its equivalent to $b=Ax$, hence $x$ is a vector of coefficients of expansion of $b$ over columns of $A$.\n",
+    "In practice, if your algorithm needs to compute a matrix inverse, you are probably doing it wrong (for example, applying inverse of a matrix to a vector is better implemented as solution of the linear system)."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "# Vector norm\n",
+    "\n",
+    "- The notions of size and distance in vector space are captured by norms \n",
+    "\n",
+    "- Norm is a measure of magnitude of a vector, denoted as $\\Vert x \\Vert$.\n",
+    "\n",
+    "The norm should satisfy certain properties:\n",
+    "\n",
+    "- $\\Vert \\alpha x \\Vert = |\\alpha| \\Vert x \\Vert$\n",
+    "- $\\Vert x + y \\Vert \\leq \\Vert x \\Vert + \\Vert y \\Vert$ (triangle inequality)\n",
+    "- If $\\Vert x \\Vert = 0$ then $x = 0$"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "source": [
+    "The distance between two vectors is then defined as\n",
+    "\n",
+    "$$ d(x, y) = \\Vert x - y \\Vert. $$\n",
+    "\n",
+    "The most well-known and widely used norm is euclidean norm:\n",
+    "\n",
+    "$$\\Vert x \\Vert_2 = \\sqrt{\\sum_{i=1}^n |x_i|^2},$$"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "## $p$-norm\n",
+    "Euclidean norm, or $2$-norm, is a subclass of an important class of $p$-norms:\n",
+    "\n",
+    "$$ \\Vert x \\Vert_p = \\Big(\\sum_{i=1}^n |x_i|^p\\Big)^{1/p}. $$"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "## Equivalence of the norms\n",
+    "All norms are equivalent in the sense that\n",
+    "\n",
+    "$$ C_1 \\Vert x \\Vert_* \\leq  \\Vert x \\Vert_{**} \\leq C_2 \\Vert x \\Vert_* $$  \n",
+    "\n",
+    "for some positive constants $C_1(n), C_2(n)$, $x \\in \\mathbb{R}^n$ for any pairs of norms $\\Vert \\cdot \\Vert_*$ and $\\Vert \\cdot \\Vert_{**}$. The equivalence of the norms means that if the vector is small in one norm, it is small in another norm. However, the constants can be large."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "## Computing norms in Python"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 47,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Relative error in L1 norm: 0.0007970883810244821\n",
+      "Relative error in L2 norm: 0.001010323277420861\n",
+      "Relative error in L_{inf} norm: 0.0033282301825079508\n"
+     ]
+    }
+   ],
+   "source": [
+    "import numpy as np\n",
+    "n = 100\n",
+    "a = np.ones(n)\n",
+    "b = a + 1e-3 * np.random.randn(n)\n",
+    "print('Relative error in L1 norm:', np.linalg.norm(a - b, 1) / np.linalg.norm(b, 1))\n",
+    "print('Relative error in L2 norm:', np.linalg.norm(a - b) / np.linalg.norm(b))\n",
+    "print('Relative error in L_{inf} norm:', np.linalg.norm(a - b, np.inf) / np.linalg.norm(b, np.inf))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "## Why $L_1$-norm can be important?\n",
+    "\n",
+    "$L_1$ norm has sparsifying property. Consider underdetermined system of equations:\n",
+    "\n",
+    "$$Ax = f,$$ where $A$ is an $n \\times m$ matrix, $A$ is known and $n\\ll m$.\n",
+    "\n",
+    "The question: can we find the solution $x$?"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "source": [
+    "Solution is not unique; a natural approach is to find the solution that is 'minimal' in some sense:\n",
+    "\n",
+    "\\begin{align*}\n",
+    "& \\Vert x \\Vert \\rightarrow \\min_x \\mbox{ subject to } Ax = f\n",
+    "\\end{align*}\n",
+    "\n",
+    "- Typical choice of $\\Vert x \\Vert = \\Vert x \\Vert_2$ leads to the solution vector of a minimal length  \n",
+    "\n",
+    "- The choice $\\Vert x \\Vert = \\Vert x \\Vert_1$ typically yields the most sparse solution vector"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "## Matrix norms\n",
+    "$\\Vert \\cdot \\Vert$ is called a matrix norm if it is a vector norm on the vector space of $m \\times n$ matrices:\n",
+    "1. $|A| \\geq 0$ and if $|A| = 0$ then $A = 0$\n",
+    "2. $|\\alpha A| = |\\alpha| |A|$\n",
+    "3. $|A+B| \\leq |A| + |B|$ (triangle inequality)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "source": [
+    "### Example: Frobenius norm"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "source": [
+    "$$\n",
+    "\\|A\\|_{\\text{F}}={\\sqrt {\\sum _{i=1}^{m}\\sum _{j=1}^{n}|a_{ij}|^{2}}}={\\sqrt {\\operatorname {trace} \\left(A^{*}A\\right)}}\n",
+    "$$"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "## Induced norms\n",
+    "\n",
+    "- The most important class of the matrix norms is the class of induced norms. They are defined as\n",
+    "\n",
+    "$$ \\Vert A \\Vert_{*} = \\sup_{x \\ne 0} \\frac{\\Vert A x \\Vert_*}{\\Vert x \\Vert_*}, $$\n",
+    "\n",
+    "where $\\Vert \\cdot \\Vert_*$ is a certain vector norm.\n",
+    "\n",
+    "- Frobenius norm is a matrix norm, but not an induced norm, i.e. you can not find $\\Vert \\cdot \\Vert_*$ which induces it."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "## Induced $p$-norms\n",
+    "\n",
+    "Important case of operator norms are matrix $p$-norms, which are defined for $\\|\\cdot\\|_* = \\|\\cdot\\|_p$. <br>\n",
+    "\n",
+    "Among all $p$-norms three norms are the most common ones:  \n",
+    "\n",
+    "- $p = 1, \\quad \\Vert A \\Vert_{1} = \\displaystyle{\\max_j \\sum_{i=1}^n} |a_{ij}|$.\n",
+    "\n",
+    "- $p = 2, \\quad$ spectral norm, denoted by $\\Vert A \\Vert_2$.\n",
+    "\n",
+    "- $p = \\infty, \\quad \\Vert A \\Vert_{\\infty} = \\displaystyle{\\max_i \\sum_{j=1}^m} |a_{ij}|$."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "## Spectral norm\n",
+    "\n",
+    "- Spectral norm, $\\Vert A \\Vert_2$ is one of the most used matrix norms (along with the Frobenius norm). \n",
+    "- It can not be computed directly from the entries using a simple formula, like the Frobenius norm, however, there are efficient algorithms to compute it.  \n",
+    "- It is directly related to the singular value decomposition (SVD) of the matrix (next lectures)."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "# Orthogonal vectors and matrices "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "source": [
+    "- A pair of vectors $x$ and $y$ is orthogonal if $x^*y=0$\n",
+    "- A set of non-zero vectors is orthogonal if its elements are pairwise orthogonal\n",
+    "- A set of non-zero vectors is orthonormal if it is orthogonal and all vectors have unit length $x^* x = 1$"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "source": [
+    "- A square complex matrix $Q$ is called unitary (orthogonal in real case) if $Q^* Q = 1$ \n",
+    "- In terms of columns: $q_i^*q_j=\\delta_{ij}$ and the columns of $Q$ form an orthonormal basis\n",
+    "- Unitary matrices preserve vector length:\n",
+    "$$\n",
+    "||Qx||_2 = ||x||_2\n",
+    "$$"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "source": [
+    "- For rectangular matrices of size $m\\times n$ ($n\\not= m$) only one of the equalities can hold\n",
+    "\n",
+    "    - $ Q^*Q = I_n$ – left unitary for $m>n$\n",
+    "    - $ QQ^* = I_m$  – right unitary for $m<n$\n",
+    "\n",
+    "- In the case of real matrices $Q^* = Q^T$ and matrices such that\n",
+    "\n",
+    "$$ Q^TQ = QQ^T = I $$\n",
+    "\n",
+    "are called orthogonal."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "source": [
+    "Important property: a product of two unitary matrices is a unitary matrix:  \n",
+    "\n",
+    "$$(UV)^* UV = V^* (U^* U) V = V^* V = I,$$"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "## Unitary invariance of $\\|\\cdot\\|_2$ and $\\|\\cdot\\|_F$ norms\n",
+    "\n",
+    "- For vector 2-norm we have already discussed that $\\Vert U z \\Vert_2 = \\Vert z \\Vert_2$ for any unitary $U$.\n",
+    "\n",
+    "- One can show that unitary matrices also do not change matrix norms $\\|\\cdot\\|_2$ and $\\|\\cdot\\|_F$, i.e. for any square $A$ and unitary $U$,$V$: \n",
+    "\n",
+    "$$ \\| UAV\\|_2 = \\| A \\|_2 \\qquad \\| UAV\\|_F = \\| A \\|_F.$$"
+   ]
+  }
+ ],
+ "metadata": {
+  "celltoolbar": "Слайд-шоу",
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.12"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/Task 1/convolutions.ipynb b/Task 1/convolutions.ipynb
new file mode 100644
index 0000000..2ddc466
--- /dev/null
+++ b/Task 1/convolutions.ipynb	
@@ -0,0 +1,113 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "import itertools"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "c = 3"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Generate some data\n",
+    "np.random.seed(42)\n",
+    "lambda1 = np.random.normal(size=(c, c))\n",
+    "lambda2 = np.random.normal(size=(c, c))\n",
+    "lambda3 = np.random.normal(size=(c, c))\n",
+    "G1 = np.random.normal(size=(c, c, c))\n",
+    "G2 = np.random.normal(size=(c, c, c))\n",
+    "U = np.random.normal(size=(c, c, c, c))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def Z_naive(lambda1, lambda2, lambda3, G1, G2, U):\n",
+    "    c = lambda1.shape[0]\n",
+    "    Z = np.zeros(shape=(c, c, c, c))\n",
+    "    for a, b, c, d, e, f, g, h, i, j in itertools.product(*([range(c)]*10)):\n",
+    "        Z[a, h, i, j] += lambda1[a, b]*lambda2[d, e]*lambda3[g, h]*G1[c, b, d]*G2[f, e, g]*U[i, j, c, f]\n",
+    "    return Z"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "198 ms ± 30.6 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)\n"
+     ]
+    }
+   ],
+   "source": [
+    "%%timeit\n",
+    "Z = Z_naive(lambda1, lambda2, lambda3, G1, G2, U)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(3, 3, 3, 3)"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "Z = Z_naive(lambda1, lambda2, lambda3, G1, G2, U)\n",
+    "Z.shape"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.7.3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/Task 1/kmeans.ipynb b/Task 1/kmeans.ipynb
new file mode 100644
index 0000000..3fbb0c1
--- /dev/null
+++ b/Task 1/kmeans.ipynb	
@@ -0,0 +1,213 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import numpy as np \n",
+    "import matplotlib.pyplot as plt "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def scatter_plot(data, col=None):\n",
+    "    from mpl_toolkits.mplot3d import Axes3D \n",
+    "    %matplotlib inline\n",
+    "    fig = plt.figure()\n",
+    "    ax = fig.add_subplot(111, projection='3d')\n",
+    "    ax.scatter(data[:,0], data[:,1], data[:,2], s = 0.5, color=col)\n",
+    "    plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "N = 1000\n",
+    "K = 3\n",
+    "d = 3\n",
+    "L = 10"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Generate some data\n",
+    "np.random.seed(42)\n",
+    "mu_true = np.random.uniform(-L, L, size = (K, d))\n",
+    "data = np.random.normal(mu_true, size = (N, K, d))\n",
+    "data = np.vstack(data)\n",
+    "np.random.shuffle(data)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "if d == 3:\n",
+    "    scatter_plot(data, None)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "mu = data[np.random.choice(range(data.shape[0]), K, replace=False)]\n",
+    "c = np.random.randint(low=0, high=K-1, size=data.shape[0])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def dist_i(x, mu):\n",
+    "    # x: N datapoints, mu: N cluster centers\n",
+    "    # returns: D_{i}, squared distances from x[i] to mu[i]\n",
+    "    dist = np.zeros(x.shape[0])\n",
+    "    for i in range(x.shape[0]):\n",
+    "        dist[i] = np.sum((x[i] - mu[i])**2)\n",
+    "    return dist\n",
+    "def dist_ij(x, mu):\n",
+    "    # x: N datapoints, mu: K cluster centers\n",
+    "    # returns: D_{ij}, squared distances from x[i] to mu[j]\n",
+    "    dist = np.zeros((x.shape[0], mu.shape[0]))\n",
+    "    for i in range(x.shape[0]):\n",
+    "        for j in range(mu.shape[0]):\n",
+    "            dist[i, j] += np.sum((x[i] - mu[j])**2)\n",
+    "    return dist"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ss_list = []\n",
+    "for n in range(10):\n",
+    "    c =  np.argmin(dist_ij(data, mu), axis = 1)    \n",
+    "    ss = np.mean(dist_i(data, mu[c]))\n",
+    "    ss_list.append(ss)    \n",
+    "    for i in range(K):\n",
+    "        cluster_members = data[c == i]\n",
+    "        cluster_members = cluster_members.mean(axis = 0)\n",
+    "        mu[i] = cluster_members"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[<matplotlib.lines.Line2D at 0x1fa6bf68ba8>]"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.plot(ss_list)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "colors = np.array([plt.cm.cool(i/(K-1)) for i in range(K)])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "if d == 3:\n",
+    "    scatter_plot(data, colors[c])"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.7.3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/Task 2/A.npy b/Task 2/A.npy
new file mode 100644
index 0000000..d9c74de
Binary files /dev/null and b/Task 2/A.npy differ
diff --git a/Task 2/Assignment_2.pdf b/Task 2/Assignment_2.pdf
new file mode 100644
index 0000000..747df25
Binary files /dev/null and b/Task 2/Assignment_2.pdf differ
diff --git a/Task 2/Lecture 2.ipynb b/Task 2/Lecture 2.ipynb
new file mode 100644
index 0000000..60e2f80
--- /dev/null
+++ b/Task 2/Lecture 2.ipynb	
@@ -0,0 +1,1472 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 45,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "skip"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "import matplotlib.pyplot as plt\n",
+    "plt.rcParams.update({\n",
+    "    \"text.usetex\": True,\n",
+    "    \"font.size\": 14,\n",
+    "    \"font.serif\": [\"Palatino\"],\n",
+    "})"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "# Matrix rank "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "source": [
+    "Matrix rank: dimension of the column space $\\equiv$ dimension of the row space"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "source": [
+    "- We have not discussed yet, how to compute the matrix rank\n",
+    "- One (the most reliable but somewhat expensive) way to compute the matrix rank is to perform its SVD decomposition \n",
+    "- Before we turn to this, lets play with the function matrix_rank from numpy"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 56,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "100"
+      ]
+     },
+     "execution_count": 56,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# A random matrix has full rank\n",
+    "import numpy as np\n",
+    "import numpy.linalg as la\n",
+    "n = 100\n",
+    "A = np.random.normal(size=(n,n))\n",
+    "la.matrix_rank(A)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "# Lets create a rank-1 matrix "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 59,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "1"
+      ]
+     },
+     "execution_count": 59,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "u = np.random.normal(size=(n, 1))\n",
+    "A = u @ u.T\n",
+    "la.matrix_rank(A)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "$A_{ij} = u_j u_j$"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 60,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "# Consider a small perturbation of A\n",
+    "delta_A = 1e-12*np.random.normal(size=(n,n))\n",
+    "Ap = A + delta_A"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 61,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([[ 0.40534717, -0.07139809],\n",
+       "       [-0.07139809,  0.0125761 ]])"
+      ]
+     },
+     "execution_count": 61,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# upper left corner of A\n",
+    "A[:2,:2]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 62,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([[ 0.40534717, -0.07139809],\n",
+       "       [-0.07139809,  0.0125761 ]])"
+      ]
+     },
+     "execution_count": 62,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# upper left corner of Ap\n",
+    "Ap[:2,:2]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 63,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "84"
+      ]
+     },
+     "execution_count": 63,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "la.matrix_rank(Ap)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "- Matrix rank is very sensitive to small perturbations of a matrix\n",
+    "- Dimensionality of a space, spanned by a set of vectors can be poorly defined\n",
+    "- Today we resolve this issue to come with a better understanding of related matrix properties"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "## What does it imply if we know that the matrix $A$ has low rank?"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "source": [
+    "Consider generic $n\\times n$ matrix $A = \\bigg[a_1\\bigg|a_2\\bigg|...\\bigg|a_n\\bigg]$:\n",
+    "- It takes $\\mathcal{O}(n^2)$ elements to store $A$\n",
+    "- It takes $\\mathcal{O}(n^2)$ FLOPs to compute $u=Av$ for a given $v$"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "source": [
+    "Consider rank-one matrix $A$\n",
+    "- It takes $\\mathcal{O}(n)$ elements to store $A$. Indeed, all columns are collinear: \n",
+    "it takes $n$ elements to store one column $a_1$ and $n-1$ elements to store the proportionality coefficients $b_i$ such that $$a_i = b_i a_1$$\n",
+    "As a result, the matrix is compressed:\n",
+    "$$\n",
+    "A_{ij} = a_i b_j\\quad\\textrm{or}\\quad A=a^T b\n",
+    "$$\n",
+    "- It takes $\\mathcal{O}(n)$ flops to compute $u=Av$ for a given $v$. Why?"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "# Low-rank approximation"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 65,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "u = np.random.normal(size=(n, 1))\n",
+    "A = u @ u.T\n",
+    "delta_A = 1e-10*np.random.normal(size=(n,n))\n",
+    "Ap = A + delta_A"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 66,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "100"
+      ]
+     },
+     "execution_count": 66,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# according to matrix_rank the rank of Ap is almost as high as it can be\n",
+    "la.matrix_rank(Ap)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 67,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "absolute error: 1.0158658489730158e-08\n",
+      "relative error: 1.2119290778015715e-10\n"
+     ]
+    }
+   ],
+   "source": [
+    "# what error do we make if we replace Ap by a rank-1 matrix A?\n",
+    "print(\"absolute error:\", np.linalg.norm(A - Ap))\n",
+    "print(\"relative error:\", np.linalg.norm(A - Ap)/np.linalg.norm(A))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "source": [
+    "- Thus, rank-1 matrix $A$ provides a very good approximation of a rank-100 matrix $Ap$\n",
+    "- It is a very synthetic example. Our goal today is to understand how this may work in a general case"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "# Geometric considerations "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "- Consider an arbitrary $m\\times n$ matrix $A$. It maps arbitrary $n$-dimensional vector $v$ to $m$-dimensional vector $u$: $u=Av$.\n",
+    "- Lets inspect the geometric meaning of this fact\n",
+    "![](geom.png)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "## Singular value decomposition\n",
+    "\n",
+    "Any $m\\times n$ matrix $A$ can be written as a product of three matrices:  \n",
+    "\n",
+    "$$ A = U \\Sigma V^*, $$\n",
+    "\n",
+    "where, for $K = \\min(m, n)$:\n",
+    "- $U$ is an $m \\times K$ matrix with orthonormal columns, \n",
+    "- $V$ is an $n \\times K$ matrix with orthonormal columns,\n",
+    "- $\\Sigma$ is a diagonal matrix with non-negative elements on the diagonal \n",
+    "\n",
+    "Reduced SVD ($m\\geq n$)\n",
+    "![](reduced.png)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "Sometimes its convenient to append the missing columns, so that both matrices ($U$ and $V$) become unitary."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "source": [
+    "Full SVD ($m\\geq n$)\n",
+    "![](full.png)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "- We can write down $A$ element-wise: $$a_{ij} = \\displaystyle{\\sum_{\\alpha=1}^r} \\sigma_\\alpha u_{i\\alpha} v_{j\\alpha}^{*}$$\n",
+    "- One usually enumerates diagonal elements of $\\Sigma$ in a descending order $\\sigma_1 \\geq  \\ldots, \\geq \\sigma_K$.\n",
+    "- If $\\text{rank}(A) = r$, then: $\\sigma_{r+1} = ... = \\sigma_K = 0.$"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "Columns of matrices $U$ and $V$ are known as left and right singular vectors.\n",
+    "They form orthonormal sets in the space of image ($u_i$) and pre-image ($v_i$) of the matrix $A$. Their geometrical meaning:\n",
+    "\n",
+    "$$\\text{ker}(A) = \\mathrm{span}\\{v_{r+1},\\dots,v_K\\}$$\n",
+    "\n",
+    "$$\\text{im}(A) = \\mathrm{span}\\{u_{1},\\dots,u_r\\}$$"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "# Eckart-Young theorem\n",
+    "\n",
+    "The best low-rank approximation can be computed by SVD.\n",
+    "\n",
+    "Let $r < \\text{rank}(A)$, $B$ is a matrix of rank $r$ (to be optimized). Then\n",
+    "\n",
+    "$$ \\min_{\\text{rank}(B)=r} \\|A - B\\|_2 = \\sigma_{r+1}. $$"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "## Low-rank approximation\n",
+    "\n",
+    "The best rank-$r$ approximation to $A$ is obtained by setting $\\sigma_{r+1}= 0, \\ldots, \\sigma_K = 0$:\n",
+    "\n",
+    "$$A_r = U_r \\Sigma_r V_r^*.$$\n",
+    "\n",
+    "The error \n",
+    "\n",
+    "$$ \\min_{\\text{rank}(B)=r} \\Vert A - B \\Vert_2 =  \\Vert A - A_r \\Vert_2 = \\sigma_{r+1}$$\n",
+    "\n",
+    "Thus the faster the singular values decay, the better is accuracy of 'compression' of the matrix into low-rank form."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "source": [
+    "The same holds for Frobenius norm:\n",
+    "$$\\min_{\\text{rank}(B)=r}\\Vert A - B \\Vert_F =  \\Vert A - A_r \\Vert_F = \\sqrt{\\sigma_{r+1}^2 + \\dots + \\sigma_{K}^2}$$"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "## Computing SVD\n",
+    "\n",
+    "- Algorithms for the computation of the SVD are tricky. Some approaches will be discussed later.\n",
+    "\n",
+    "- We are ready to use NumPy and SciPy implementations\n",
+    "\n",
+    "- Broadly speaking, one may think of (i) exact computation of complete SVD, (ii) exact computation of 'sparse' SVD,  where we need only first $k \\ll n$ singular values and vectors and (iii) randomized SVD (approximate evaluation of the leading subset of singular values and vectors)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 68,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Rank of the matrix: 1\n",
+      "Rank of the matrix: 100\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Recall: Computing matrix rank\n",
+    "import numpy as np\n",
+    "print('Rank of the matrix:', np.linalg.matrix_rank(A))\n",
+    "print('Rank of the matrix:', np.linalg.matrix_rank(Ap))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 69,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([[ 0.62881492, -0.38142909],\n",
+       "       [-0.38142909,  0.2313688 ]])"
+      ]
+     },
+     "execution_count": 69,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "A[:2,:2]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 70,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([[ 0.62881492, -0.38142909],\n",
+       "       [-0.38142909,  0.2313688 ]])"
+      ]
+     },
+     "execution_count": 70,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "Ap[:2,:2]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 74,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "u, s, vh = np.linalg.svd(A)\n",
+    "up, sp, vhp = np.linalg.svd(Ap)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "la.matrix_rank()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 75,
+   "metadata": {
+    "scrolled": true,
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([8.38222193e+01, 4.53158462e-14, 4.00097651e-14, 3.10833486e-14,\n",
+       "       2.59425086e-14, 2.13154110e-14, 2.07592143e-14, 1.90293475e-14,\n",
+       "       1.77971365e-14, 1.46656957e-14])"
+      ]
+     },
+     "execution_count": 75,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "s[:10]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 73,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([8.38222193e+01, 1.99954677e-09, 1.89619187e-09, 1.86088354e-09,\n",
+       "       1.84812585e-09, 1.81777344e-09, 1.75761017e-09, 1.75596734e-09,\n",
+       "       1.68481081e-09, 1.66847435e-09])"
+      ]
+     },
+     "execution_count": 73,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "sp[:10]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "source": [
+    "SVD allows to properly define a numerical rank for a given tolerance $\\epsilon$"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "## Singular values of a random Gaussian matrix\n",
+    "\n",
+    "What is the singular value decay of a random matrix?"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 864x288 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt\n",
+    "n = 1000\n",
+    "a = np.random.randn(n, n)\n",
+    "s = np.linalg.svd(a, compute_uv=False)\n",
+    "fig, ax = plt.subplots(1, 2, figsize=(12, 4))\n",
+    "ax[0].plot(s/s[0])\n",
+    "ax[1].plot(s/s[0])\n",
+    "ax[1].set_yscale('log')\n",
+    "ax[0].set_ylabel(r\"$\\sigma_i / \\sigma_0$\", fontsize=16)\n",
+    "ax[0].set_xlabel(r\"$i$\", fontsize=16)\n",
+    "ax[1].set_xlabel(r\"$i$\", fontsize=16);"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "# Applications of SVD"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "source": [
+    "## Dense matrix compression\n",
+    "\n",
+    "Dense matrices require $N^2$ elements to be stored. A rank-$r$ approximation can reduces this number of $\\mathcal{O}(Nr)$. Let us consider image compression as an example."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 76,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "from skimage import data\n",
+    "from skimage.color import rgb2gray\n",
+    "from numpy.linalg import svd\n",
+    "from skimage import img_as_float"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 77,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "cat = rgb2gray(img_as_float(data.chelsea()))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 80,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(300, 451)"
+      ]
+     },
+     "execution_count": 80,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cat.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 78,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([[0.48523098, 0.48523098, 0.47738784, 0.47738784, 0.47738784],\n",
+       "       [0.49699569, 0.49307412, 0.48523098, 0.48130941, 0.48130941],\n",
+       "       [0.50849255, 0.50457098, 0.49475569, 0.49083412, 0.49307412],\n",
+       "       [0.52054   , 0.51269686, 0.50485373, 0.50485373, 0.50064941],\n",
+       "       [0.52894863, 0.52110549, 0.51661843, 0.51269686, 0.50849255]])"
+      ]
+     },
+     "execution_count": 78,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cat[:5, :5]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 81,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.image.AxesImage at 0x2826347c400>"
+      ]
+     },
+     "execution_count": 81,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.imshow(cat)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 83,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "U, s, Vc = svd(cat, full_matrices=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 88,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "def compress_and_show(k):\n",
+    "    os = cat.shape\n",
+    "    cat_compressed = U[:,:k] @ np.diag(s[:k]) @ Vc[:k,:]\n",
+    "    compression_ratio = 100.0* (k*(os[0] + os[1])+k)/(os[0]*os[1])\n",
+    "    plt.title(\"compression ratio={:.2f}\".format(compression_ratio)+\"%\")\n",
+    "    plt.imshow(cat_compressed)\n",
+    "    plt.axis('off')\n",
+    "    plt.tight_layout()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 90,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "compress_and_show(200)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 91,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 864x288 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig, ax = plt.subplots(1, 2, figsize=(12, 4))\n",
+    "ax[0].plot(s)\n",
+    "ax[1].plot(s)\n",
+    "ax[1].set_yscale('log')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 92,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "compress_and_show(50)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "# Applications of SVD "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "source": [
+    "## Principal Component Analysis (PCA)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "Consider a dataset of points."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "source": [
+    "![](https://i.stack.imgur.com/jPw90.png)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "source": [
+    "The two 'properties' of each point in the sample ($x$ and $y$ on this plot) are correlated. Let us think of some new 'property', given by a linear combination $w_1 x + w_2 y$. PCA looks for properties that show as much variation across the data points as possible. Equivalently, PCA looks for properties that allow to reconstruct the original characteristics as well as possible."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "Consider projection of the data points onto a certain (single) direction. Where should one project to maintain the largest variety of the datapoint? Related question: whats the best linear fit?"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "source": [
+    "![](https://i.stack.imgur.com/lNHqt.gif)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "### Formally:\n",
+    "The first component should be defined in order to maximize variance. The projections of datapoints $\\mathbf  {a}_{{(i)}}$ onto the vector ${\\mathbf  {w}}$ are given by $\\mathbf  {a}_{{(i)}}\\cdot {\\mathbf  {w}}$. Suppose we've already standardized the data, then we need to solve the following optimization problem:\n",
+    "$$\n",
+    "{\\underset  {\\Vert {\\mathbf  {w}}\\Vert =1}{\\operatorname {\\arg \\,max}}}\\,\\left\\{\\sum _{i}\\left({\\mathbf  {a}}_{{(i)}}\\cdot {\\mathbf  {w}}\\right)^{2}\\right\\}\n",
+    "$$\n",
+    "\n",
+    "or, combining vectors $\\mathbf  {a}_{{(i)}}$ into the rows of the matrix $\\mathbf {A}$, we may write:\n",
+    "\n",
+    "$$\n",
+    "{\\underset {\\Vert \\mathbf {w} \\Vert =1}{\\operatorname {\\arg \\,max} }}\\,\\{\\Vert \\mathbf {Aw} \\Vert ^{2}\\}={\\underset {\\Vert \\mathbf {w} \\Vert =1}{\\operatorname {\\arg \\,max} }}\\,\\left\\{\\mathbf {w} ^{\\top}\\mathbf {A^{\\top}} \\mathbf {Aw} \\right\\}\n",
+    "$$"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "The key ingridient is the matrix $A^T A$, proportional to the empirical covariance matrix. It is known that for positive semidefinite matrix $A^\\top A$ the solution is delivered by the eigenvector of $A^\\top A$, corresponding to the largest eigenvalue. We can repeat this procedure and construct another direction, explaining as much variance in orthogonal directions. So, we can conclude, that the following linear operation ($n$ stays for the number of observation points and $d$ for the dimensions of observation vectors):\n",
+    "\n",
+    "$$\n",
+    "\\underset{n \\times d}{A} \\longrightarrow \\underset{n \\times k}{A^\\prime} = \\underset{n \\times d}{A} \\cdot \\underset{d \\times k}{W} \n",
+    "$$\n",
+    "\n",
+    "describes the projection of data onto the $k$ principal components, where $W$ contains first (by the size of eigenvalues) $k$ eigenvectors of $A^\\top A$"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "Formally, we may start with SVD decomposition of $A$:\n",
+    "\n",
+    "$$A = U \\Sigma W^\\top$$\n",
+    "\n",
+    "Then, consider matrix $A^\\top A$:\n",
+    "\n",
+    "$$A^\\top A=W \\Sigma^2 W^\\top$$\n",
+    "\n",
+    "Which corresponds to the eigendecomposition of matrix $A^\\top A$, where $W$ stands for the matrix of eigenvectors of $A^\\top A$, while $\\Sigma^2$ contains eigenvalues of $A^\\top A$. In other words, columns of $W$ are right singular vectors of $A$.\n",
+    "\n",
+    "In the end:\n",
+    "$$\n",
+    "A \\longrightarrow A \\cdot W = U \\Sigma W^\\top W = U \\Sigma\n",
+    "$$\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "# Example of dimensionality reduction via PCA: Wine dataset"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 93,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt\n",
+    "from sklearn.datasets import load_wine\n",
+    "from sklearn.preprocessing import StandardScaler"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 94,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "(178, 13) \n",
+      "\n",
+      "[0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
+      " 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1\n",
+      " 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1\n",
+      " 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2\n",
+      " 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2]\n"
+     ]
+    }
+   ],
+   "source": [
+    "wine = load_wine()\n",
+    "\n",
+    "A = wine['data']\n",
+    "print(wine['data'].shape, \"\\n\")\n",
+    "\n",
+    "labels = wine['target']\n",
+    "print(labels)\n",
+    "\n",
+    "classes = [0, 1, 2]\n",
+    "colors = ['red', 'green', 'blue']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 95,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "# data standardization\n",
+    "A_std = StandardScaler().fit_transform(A)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 97,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([[ 1.51861254, -0.5622498 ,  0.23205254],\n",
+       "       [ 0.24628963, -0.49941338, -0.82799632],\n",
+       "       [ 0.19687903,  0.02123125,  1.10933436],\n",
+       "       [ 1.69154964, -0.34681064,  0.4879264 ],\n",
+       "       [ 0.29570023,  0.22769377,  1.84040254],\n",
+       "       [ 1.48155459, -0.51736664,  0.30515936],\n",
+       "       [ 1.71625494, -0.4186237 ,  0.30515936],\n",
+       "       [ 1.3086175 , -0.16727801,  0.89001391],\n",
+       "       [ 2.25977152, -0.62508622, -0.7183361 ],\n",
+       "       [ 1.0615645 , -0.88540853, -0.352802  ]])"
+      ]
+     },
+     "execution_count": 97,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "A_std[:10,:3]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "source": [
+    "How can we visually inspect the dataset? Recall that we have 178 datapoints in 13-dimensional space. What if we reduce dimension in some random way? Lets pick two random features."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 98,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[0 3]\n"
+     ]
+    }
+   ],
+   "source": [
+    "rank = 2\n",
+    "ix = np.random.choice(A.shape[1], 2, replace=False)\n",
+    "print(ix)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 99,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "def inspect_projections(projections):\n",
+    "    for label, colour in zip(classes, colors):\n",
+    "        plt.scatter(projections[labels == label, 0],\n",
+    "                    projections[labels == label, 1],\n",
+    "                    label = label,\n",
+    "                    c = colour)\n",
+    "    plt.legend(loc='best')\n",
+    "    plt.grid()\n",
+    "    plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 100,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "rnd_projections = A[:, ix]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 102,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "inspect_projections(rnd_projections)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "## Lets use PCA for (unsupervised) projection "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 103,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "u, s, wh = np.linalg.svd(A_std)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 115,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "cum_s = np.cumsum(s**2)\n",
+    "plt.plot(cum_s/cum_s[-1], color = 'black')\n",
+    "plt.bar(x=np.arange(len(s)), height=s**2/cum_s[-1]);"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "source": [
+    "Lets project onto the principal components: $A \\longrightarrow  U \\Sigma$"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 110,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "projections = u[:,:rank] @ np.diag(s[:rank])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 111,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "inspect_projections(projections)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "source": [
+    "Its clear that projections obtained by SVD capture the data variety much better than just two random columns. The resulting projections can be fed to your favourite classification algorithm. In this case, we reduced (in an unsupervised manner) the data in 13-dimensional space to the data in 2-dimensional space!"
+   ]
+  }
+ ],
+ "metadata": {
+  "celltoolbar": "Slideshow",
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.12"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}