presentations/szisz30/szisz30slides.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true,
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [],
   "source": [
    "%load_ext autoreload\n",
    "%autoreload 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true,
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [],
   "source": [
    "import random\n",
    "from collections import Counter\n",
    "from IPython.display import display\n",
    "\n",
    "import szisz30"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Kiszámítható egyéniségek\n",
    "<i>Fülöp András</i>\n",
    "\n",
    "<b>SZISZ30 konferencia</b>, 2017 június 10."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Magamról\n",
    "\n",
    "- Data Scientist @ Lensa/Gitential\n",
    "- SzISz-ben oktató ~4. éve\n",
    "    - 7 Python kurzus\n",
    "    - 2 Data Science kurzus"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Python\n",
    "\n",
    "> *A programozás a legközelebbi dolog a szupererőhöz.*  \n",
    "> Drew Houston (Dropbox)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Boldog szülinapot SZISZ!\n"
     ]
    }
   ],
   "source": [
    "print \"Boldog szülinapot SZISZ!\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Kő-papír-olló\n",
    "<img src=\"pics/rock.gif\" align='left'/>\n",
    "<img src=\"pics/paper.gif\" align='left'/>\n",
    "<img src=\"pics/scissors.gif\" align='left'/>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "<img src=\"pics/janken.gif\" />"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'ollo'"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hands = ['ko', 'papir', 'ollo']\n",
    "random.choice(hands)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
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2oSvng6tAdXX76wi4GNYPuqo71tDFwt/uBnFVVZV+9rOf6aGHHtLYsWOVkpKiYcOGSZJS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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x42adb38>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "games = []\n",
    "for _ in range(10000):\n",
    "    games.append(random.choice(hands))\n",
    "    \n",
    "szisz30.plot_freqs(Counter(games))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Jósolható a taktikánk?\n",
    "\n",
    "<img src=\"pics/rock.gif\" align='left'/>\n",
    "<img src=\"pics/paper.gif\" align='left'/>\n",
    "<img src=\"pics/paper.gif\" align='left'/>\n",
    "<img src=\"pics/scissors.gif\" align='left'/>\n",
    "<img src=\"pics/rock.gif\" align='left'/>\n",
    "<img src=\"pics/rock.gif\" align='left'/>\n",
    "<img src=\"pics/rock.gif\" align='left'/>\n",
    "<img src=\"pics/paper.gif\" align='left'/>\n",
    "<img src=\"pics/scissors.gif\" align='left'/>\n",
    "<img src=\"pics/rock.gif\" align='left'/>\n",
    "<img src=\"pics/paper.gif\" align='left'/>\n",
    "<img src=\"pics/scissors.gif\" align='left'/>\n",
    "<img src=\"pics/paper.gif\" align='left'/>\n",
    "<img src=\"pics/paper.gif\" align='left'/>\n",
    "<img src=\"pics/rock.gif\" align='left'/>\n",
    "<img src=\"pics/rock.gif\" align='left'/>\n",
    "<img src=\"pics/scissors.gif\" align='left'/>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "my_play = 'kppokkkpokpoppkko'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "# Véletlenszerű MI"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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AEOEFAMAQ4QUAwBDhBQDAEOEFAMAQ4QUAwBDhBQDAEOEFAMAQ4QUAwBDhBQDAEOEFAMAQ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\nhBcAAEOEFwAAQ4QXAABD/wtPhNr6qU6MMwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xba9d7f0>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rnd = szisz30.RPS('null', 42)\n",
    "rnd.play(my_play, plot=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0xb4fcac8>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rnd.plot_probs()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "# Naív MI\n",
    "\n",
    "A gyakrabban használt kezeket jegyezzük meg"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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WKRP6acvbp3Tk02IPT+YbiCwAtGAXiv/5Ob7+/l+9gnjpyjVdvVblqZF8CpEFAEiSTnx2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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xc162240>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "naive = szisz30.RPS('naive', 42)\n",
    "naive.play(my_play, plot=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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QCATD/Ilbb71VCxcuVG5url5//fVe+/j9fsXFxYUcyKFDnf/q2DGEtLaG/gYPOBOOoYGT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\nDKYrW4aL/wAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xc297f28>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "naive.plot_probs()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "# Emlékező MI\n",
    "\n",
    "Jegyezzük meg, hogy milyen kezek után mik következnek"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "<img src=\"pics/stateful.png\" width=400 align='left'/>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "stateful = szisz30.RPS('stateful', 42)\n",
    "stateful2 = szisz30.RPS('stateful', 42, 2)\n",
    "stateful3 = szisz30.RPS('stateful', 42, 3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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Ef/zjH6/YlpqaWu/DAADg6bj4FgAAgwgvAAAGEV4AAAwivAAAGER4AQAwiPACAGAQ4QUA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\nIMILAIBBhBcAAIP+H/NMsVD2clXkAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xda4e278>"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stateful2.play(my_play)\n",
    "stateful3.play(my_play)\n",
    "stateful.play(my_play, plot=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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cBrhZBwAAhlDCAAAYQgkDAGAIJQwAgCGUMAAAhlDCAAAY4vcjSmhvTu5a0xEk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\nSUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xe5d0ef0>"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stateful.plot_probs()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Gépek csatája"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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VquXLlystLU1eXl6aO3euevXqpZycHLfHAgAA99QZ782bNysgIEAvv/yySkpKNHLkSHXv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\nAAxDvAEAMAzxBgDAMP8f9FzpRmTqHuAAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xeeb07f0>"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "szisz30.Simulate(stateful, stateful3, 50000, p1static=True, p2static=False).play(plot=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Neurális hálózatok\n",
    "\n",
    "## Perceptron model\n",
    "<img src=\"pics/neuron.png\" width=400 align=\"left\"/>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "## Többrétegű hálózat\n",
    "<img src=\"pics/mlp.png\" width=400 align=\"left\" source=\"https://github.com/nikolaypavlov/MLPNeuralNet\">"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "# Mélytanulás"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "<img src=\"pics/mgc.gif\"/>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "<img src=\"pics/deepdream.jpg\" source=\"https://artofericwayne.com/2015/07/08/google-deep-dream-getting-too-good/\"/>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "<img src=\"pics/deeprebrandt.jpg\" source=\"http://www.wired.co.uk/article/new-rembrandt-painting-computer-3d-printed\"/>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "<img src=\"pics/deeptransform.jpg\" source=\"https://deepart.io/\"/>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "> *PANDARUS:*  \n",
    "> *Alas, I think he shall be come approached and the day*  \n",
    "> *When little srain would be attain'd into being never fed,*  \n",
    "> *And who is but a chain and subjects of his death,*  \n",
    "> *I should not sleep.*  \n",
    "> ...  \n",
    ">   \n",
    "> *Clown:*  \n",
    "> *Come, sir, I will make did behold your worship.*  \n",
    ">   \n",
    "> *VIOLA:*  \n",
    "> *I'll drink it.*  \n",
    "\n",
    "\\- William RNNspear"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "<img src=\"pics/deeppaper.jpg\" source=\"http://karpathy.github.io/2015/05/21/rnn-effectiveness/\">"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Neurális MI"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "nn = szisz30.RPS('neural', 42)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x105618d0>"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nn.play(my_play, plot=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Demo"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "074af8ceade14b57a4af5d16b114f86a"
      }
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display(szisz30.generate_interface(nn))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAeQAAAFXCAYAAABz8D0iAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xf9cc940>"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nn.plot_win_ratio()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Ajánló rendszerek\n",
    "\n",
    "<img src=\"pics/logos.png\">"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "# Collaborative filtering\n",
    "\n",
    "<img src=\"pics/cfinteract.png\" />"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "<img src=\"pics/cfmatrix.png\" />"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "# Tartalom alapú módszerek \n",
    "\n",
    "<img src=\"pics/cbinteract.png\" />"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# A nagy testvér figyel?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Köszönöm megtisztelő figyelmüket!\n",
    "\n",
    "<img src=\"pics/twitter.png\" align='left' style='margin-right: 5px; margin-left: 15px' /><b>twitter.com/fulibacsi</b><br>\n",
    "\n",
    "<img src=\"pics/github.png\" align='left' style='margin-right: 5px; margin-left: 15px' /><b>github.com/fulibacsi</b>"
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    "**Források:**\n",
    "\n",
    "- Deep learning képek:\n",
    "    - deep dream: https://artofericwayne.com/2015/07/08/google-deep-dream-getting-too-good/\n",
    "    - Rembrandt 3d nyomtatás: http://www.wired.co.uk/article/new-rembrandt-painting-computer-3d-printed\n",
    "    - Képek átalakítása festői stílusokban: https://deepart.io/\n",
    "    - Generatív nyelvek: http://karpathy.github.io/2015/05/21/rnn-effectiveness/\n",
    "- Neurális Kő-Papír-Olló ágensek:\n",
    "    - https://www.his.se/PageFiles/8158/Henrik_Engstrom.pdf\n",
    "    - http://act-r.psy.cmu.edu/wordpress/wp-content/uploads/2012/12/874paper203.pdf\n",
    "- Hogyan nyerjünk emberi ellenfél ellen: http://blog.wolfram.com/2014/01/20/how-to-win-at-rock-paper-scissors/\n",
    "- RoChamBo - Kő-Papír-Olló MI bajnokság:\n",
    "    - https://github.com/NavjotMinhas/RockPaperScissors_AI\n",
    "    - https://www.reddit.com/r/gamedev/comments/doxb3/simple_ai_for_a_rockpaperscissors_game/\n",
    "    - http://webdocs.cs.ualberta.ca/~darse/rsbpc.html"
   ]
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