{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "![](images/EscUpmPolit_p.gif \"UPM\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Course Notes for Learning Intelligent Systems" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Department of Telematic Engineering Systems, Universidad Politécnica de Madrid, © Carlos A. Iglesias" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Exercises" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Table of Contents\n", "\n", "* [Exercises](#Exercises)\n", "\t* [Exercise 1 - Sentiment classification for Twitter](#Exercise-1---Sentiment-classification-for-Twitter)\n", "\t* [Exercise 2 - Spam classification](#Exercise-2---Spam-classification)\n", "\t* [Exercise 3 - Automatic essay classification](#Exercise-3---Automatic-essay-classification)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Exercises" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Here we propose several exercises, it is recommended to work only in one of them." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Exercise 1 - Sentiment Analysis on Movie Reviews" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "You can try the exercise Exercise 2: Sentiment Analysis on movie reviews of Scikit-Learn https://scikit-learn.org/stable/tutorial/text_analytics/working_with_text_data.htmlt\n", "* Previously you should follow the installation instructions in the section 'Tutorial Setup'", ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Exercise 2 - Spam classification" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The classification of spam is a classical problem. [Here](http://zacstewart.com/2015/04/28/document-classification-with-scikit-learn.html) you can find a detailed example of how to do it using the datasets Enron-Spama and SpamAssassin. You can try to test yourself the classification." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Exercise 3 - Automatic essay classification" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "As you have seen, we did not got great results in the previous notebook. You can try to improve them." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Licence" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The notebook is freely licensed under under the [Creative Commons Attribution Share-Alike license](https://creativecommons.org/licenses/by/2.0/). \n", "\n", "© Carlos A. Iglesias, Universidad Politécnica de Madrid." ] } ], "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": "3.7.1" }, "latex_envs": { "LaTeX_envs_menu_present": true, "autocomplete": true, "bibliofile": "biblio.bib", "cite_by": "apalike", "current_citInitial": 1, "eqLabelWithNumbers": true, "eqNumInitial": 1, "hotkeys": { "equation": "Ctrl-E", "itemize": "Ctrl-I" }, "labels_anchors": false, "latex_user_defs": false, "report_style_numbering": false, "user_envs_cfg": false } }, "nbformat": 4, "nbformat_minor": 1 }