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| { | |
| "cells": [ | |
| { | |
| "cell_type": "code", | |
| "execution_count": 15, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [], | |
| "source": [ | |
| "import numpy as np\n", | |
| "import sklearn\n", | |
| "import matplotlib.pyplot as plt \n", | |
| "%matplotlib inline " | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "Un gros titre \n", | |
| "--\n", | |
| "\n", | |
| "$K=\\alpha \\times \\beta $\n", | |
| "Là tu peux écrire ce que tu veux \n", | |
| "\n", | |
| "On peut mettre des [liens](http://www.brain.bzh)\n", | |
| "\n", | |
| "Voilà comment mettre des trucs en **gras**" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 17, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "image/png": 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GAS85ncVpxpgo4GzgZQBrba219pCzqRwXCoQbY0KBCKDI4Txe5yvFfbwXJA7a\novo2Y0wcMBhY42wSRz0FTAVcTgfxAfFAMfDq0UtHLxljWjgdyinW2l3AE8BOYDdQaq1d6Wwq7/OV\n4pbjMMa0BFKBu6y1ZU7ncYIx5jJgn7V2ndNZfEQoMAR43lo7GKgAgvZ3QsaYNhz513k8EAO0MMZc\n72wq7/OV4nbrBYmDiTGmKUdK+y1rbZrTeRw0BrjcGLOdI5fQzjfGvOlsJEcVAoXW2n//C2w+R4o8\nWI0Ftllri621dUAaMNrhTF7nK8WtFyT+FmOM4cg1zBxr7ZNO53GStXa6tbartTaOI98XH1prA/6M\n6vtYa/cABcaYvkffdQGQ7WAkp+0ERhpjIo7+3FxAEPyy1q3XnPQ2vSDx/xgD3ABkGGM2HH3fjKOv\n/Snya+Ctoyc5+cAtDudxjLV2jTFmPrCeI8/G+oYguItSd06KiPgZX7lUIiIiblJxi4j4GRW3iIif\nUXGLiPgZFbeIiJ9RcYuI+BkVt4iIn1Fxi4j4mf8HFYFfB07ZR/EAAAAASUVORK5CYII=\n", | |
| "text/plain": [ | |
| "<matplotlib.figure.Figure at 0x7f80a7386fd0>" | |
| ] | |
| }, | |
| "metadata": {}, | |
| "output_type": "display_data" | |
| } | |
| ], | |
| "source": [ | |
| "plt.plot(range(10))\n", | |
| "plt.show()" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": null, | |
| "metadata": { | |
| "collapsed": true | |
| }, | |
| "outputs": [], | |
| "source": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": null, | |
| "metadata": { | |
| "collapsed": true | |
| }, | |
| "outputs": [], | |
| "source": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": null, | |
| "metadata": { | |
| "collapsed": true | |
| }, | |
| "outputs": [], | |
| "source": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": null, | |
| "metadata": { | |
| "collapsed": true | |
| }, | |
| "outputs": [], | |
| "source": [] | |
| } | |
| ], | |
| "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": "3.6.1" | |
| } | |
| }, | |
| "nbformat": 4, | |
| "nbformat_minor": 2 | |
| } |
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