mirror of
https://github.com/gsi-upm/sitc
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156 lines
3.7 KiB
Plaintext
156 lines
3.7 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"![](images/EscUpmPolit_p.gif \"UPM\")"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Course Notes for Learning Intelligent Systems"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Department of Telematic Engineering Systems, Universidad Politécnica de Madrid, © Carlos A. Iglesias"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Exercises"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Table of Contents\n",
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"\n",
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"* [Exercises](#Exercises)\n",
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"\t* [Exercise 1 - Sentiment Analysis on Movie Reviews](#Exercise-1---Sentiment-Analysis-on-Movie-Reviews)\n",
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"\t* [Exercise 2 - Spam classification](#Exercise-2---Spam-classification)\n",
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"\t* [Exercise 3 - Automatic essay classification](#Exercise-3---Automatic-essay-classification)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Exercises"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Here we propose several exercises, it is recommended to work only in one of them."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Exercise 1 - Sentiment Analysis on Movie Reviews"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"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.html. \n",
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"Previously you should follow the installation instructions in the section Tutorial Setup."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Exercise 2 - Spam classification"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"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."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Exercise 3 - Automatic essay classification"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"As you have seen, we did not got great results in the previous notebook. You can try to improve them."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Licence"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"The notebook is freely licensed under under the [Creative Commons Attribution Share-Alike license](https://creativecommons.org/licenses/by/2.0/). \n",
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"\n",
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"© Carlos A. Iglesias, Universidad Politécnica de Madrid."
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.7.1"
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},
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"latex_envs": {
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"LaTeX_envs_menu_present": true,
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"autocomplete": true,
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"bibliofile": "biblio.bib",
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"cite_by": "apalike",
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"current_citInitial": 1,
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"eqLabelWithNumbers": true,
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"eqNumInitial": 1,
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"hotkeys": {
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"equation": "Ctrl-E",
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"itemize": "Ctrl-I"
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},
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"labels_anchors": false,
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"latex_user_defs": false,
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"report_style_numbering": false,
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"user_envs_cfg": false
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}
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},
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"nbformat": 4,
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"nbformat_minor": 1
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}
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