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121 lines
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121 lines
3.6 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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"![](files/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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"## [Introduction to Machine Learning](2_0_0_Intro_ML.ipynb)"
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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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"# Introduction to Machine Learning\n",
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"\n",
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"This lecture provides a quick introduction to Machine Learning in Python using the Iris dataset as an example. In this session we will focus on applying multiclass classification algorithms.\n",
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"\n",
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"The main objectives of this session are:\n",
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"\n",
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"* Learn to use scikit-learn\n",
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"* Learn the basic steps to apply machine learning techniques: dataset analysis, load, preprocessing, training, validation, optimization and persistence.\n",
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"* Learn how to do a exploratory data analysis\n",
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"* Learn how to visualise a dataset\n",
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"* Learn how to load a bundled dataset\n",
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"* Learn how to separate the dataset into traning and testing datasets\n",
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"* Learn how to train a classifier\n",
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"* Learn how to predict with a trained classifier\n",
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"* Learn how to evaluate the predictions\n",
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"* Learn how to optimize the configuration of a classifier\n",
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"* Learn how to save a model\n"
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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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"## References"
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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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"* [Scikit-learn web page](http://scikit-learn.org/stable/)\n",
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"* [Scikit-learn videos](http://blog.kaggle.com/author/kevin-markham/) and [notebooks](https://github.com/justmarkham/scikit-learn-videos) by Kevin Marham\n",
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"* [Learning scikit-learn: Machine Learning in Python](http://proquest.safaribooksonline.com/book/programming/python/9781783281930/1dot-machine-learning-a-gentle-introduction/ch01s02_html), Raúl Garreta; Guillermo Moncecchi, Packt Publishing, 2013.\n",
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"* [Python Machine Learning](http://proquest.safaribooksonline.com/book/programming/python/9781783555130), Sebastian Raschka, Packt Publishing, 2015."
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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\n",
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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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"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": "3.5.5"
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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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"equation": "Ctrl-E",
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"itemize": "Ctrl-I"
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