Updated files

Code/chapter_4.ipynb

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+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 53,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "\n",
+    "# create user preferences\n",
+    "user_pref = np.array([5, 1, 3])\n",
+    "\n",
+    "# create a random movie matrix of 10,000 movies\n",
+    "movies = np.random.randint(5,size=(3,1000))+1\n",
+    "\n",
+    "# Note that the randint will make random integers from 0-4\n",
+    "# so I added a 1 at the end to increase the scale from 1-5"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 54,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "(3,)\n",
+      "(3, 1000)\n"
+     ]
+    }
+   ],
+   "source": [
+    "print user_pref.shape # (1, 3)\n",
+    "\n",
+    "print movies.shape    # (3, 1000)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 55,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "# np.dot does both dot products and matrix multiplication\n",
+    "recs = np.dot(user_pref, movies)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 76,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "0.000160932540894 seconds to run 10000 movies\n",
+      "0.00121188163757 seconds to run 100000 movies\n",
+      "0.0105860233307 seconds to run 1000000 movies\n",
+      "0.096577167511 seconds to run 10000000 movies\n",
+      "4.16197991371 seconds to run 100000000 movies\n"
+     ]
+    }
+   ],
+   "source": [
+    "import time\n",
+    "\n",
+    "for i in (10000, 100000, 1000000, 10000000, 100000000):\n",
+    "    movies = np.random.randint(5,size=(3,i))+1\n",
+    "    now = time.time()\n",
+    "    np.dot(user_pref, movies)\n",
+    "    print (time.time() - now), \"seconds to run\", i, \"movies\"\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 72,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "10.0056350231\n"
+     ]
+    }
+   ],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 2",
+   "language": "python",
+   "name": "python2"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 2
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython2",
+   "version": "2.7.6"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}