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<!doctype html>
<html lang="en">
<head>
<meta charset="utf-8">
<title>Machine Learning - Introduction</title>
<meta name="description" content="Introduction to Machine Learning">
<meta name="author" content="Piero Savastano">
<meta name="apple-mobile-web-app-capable" content="yes">
<meta name="apple-mobile-web-app-status-bar-style" content="black-translucent">
<meta name="viewport" content="width=device-width, initial-scale=1.0, maximum-scale=1.0, user-scalable=no, minimal-ui">
<link rel="icon" type="image/x-icon" href="favicon.ico">
<link rel="stylesheet" href="css/reveal.css">
<link rel="stylesheet" href="css/theme/moon.css" id="theme">
<link rel="stylesheet" href="css/pieroit.css">
<!-- Code syntax highlighting -->
<link rel="stylesheet" href="lib/css/zenburn.css">
<!-- Printing and PDF exports -->
<script>
var link = document.createElement( 'link' );
link.rel = 'stylesheet';
link.type = 'text/css';
link.href = window.location.search.match( /print-pdf/gi ) ? 'css/print/pdf.css' : 'css/print/paper.css';
document.getElementsByTagName( 'head' )[0].appendChild( link );
</script>
<!--[if lt IE 9]>
<script src="lib/js/html5shiv.js"></script>
<![endif]-->
</head>
<body>
<div class="reveal">
<!-- Any section element inside of this container is displayed as a slide -->
<div class="slides">
<!-- Intro -->
<section>
<h1><a href="index.html">Machine Learning</a></h1>
<h2>Introduction</h2>
</section>
<!-- Definition -->
<section data-background="img/hal.svg">
<h2>What is machine learning?</h2>
<section>
<br/><br/><br/><br/><br/><br/><br/><br/>
<blockquote>
Field of study that gives computers the ability to learn without being explicitly programmed.
</blockquote>
Arthur Samuel
</section>
<section>
<br/><br/><br/><br/><br/><br/><br/><br/>
<blockquote>
A computer program is said to learn from experience E with respect to some class of tasks T and performance measure P if its performance at tasks in T, as measured by P, improves with experience E".
</blockquote>
Tom M. Mitchell
</section>
<section>
<br/><br/><br/><br/><br/><br/><br/><br/>
<blockquote>
The science and engineering of making intelligent machines.
</blockquote>
John McCarthy about A.I.
</section>
</section>
<!-- Teaser and known applications -->
<section>
<h2>Why so important?</h2>
<section>
<h3>To automate</h3>
<div>ML infers rules from data<br/>
(implicit programming)
</div>
</section>
<section>
<h3>To make machines smart!</h3>
<span>
<a href="https://upload.wikimedia.org/wikipedia/commons/b/be/Deep_Blue.jpg">
<img height="300px" src="img/Deep_Blue.jpg" />
</a>
</span>
<span>
<a href="https://en.wikipedia.org/wiki/Deep_Blue_versus_Garry_Kasparov">
<img height="300px" src="img/kasparov.png" />
</a>
</span>
<p>what is <i>smart</i>? What is <i>intelligent</i>?</p>
</section>
<section>
<h3>Computer vision</h3>
<a href="https://i.ytimg.com/vi/9pl4tsqVwdc/hqdefault.jpg">
<img src="img/computer_vision.jpg" />
</a>
</section>
<section>
<h3>Diagnostics</h3>
<a href="https://en.wikipedia.org/wiki/Bayesian_network">
<img src="img/bayes_net.svg" />
</a>
</section>
<section>
<h3>Recommendation</h3>
<a href="http://www.amazon.com/">
<img src="img/amazon_recommendations.png" />
</a>
</section>
<section>
<h3>Coming soon...</h3>
<span>
<a href="https://i.ytimg.com/vi/dOkLK_bRhxk/hqdefault.jpg">
<img width="250px" src="img/asimo.jpg" />
</a>
</span>
<span>
<a href="https://c2.staticflickr.com/2/1586/24734777053_3479b886e1_b.jpg">
<img width="250px" src="img/boston_dynamics.jpg" />
</a>
</span>
<span>
<a href="https://research.google.com/">
<img width="250px" src="img/google_car.jpg" />
</a>
</span>
</section>
</section>
<section>
<h2>Robot revolution?</h2>
<div class="half">
<a href="http://www.amazon.com/The-Second-Machine-Age-Technologies/dp/0393239357">
<img width="300px" src="img/the_second_machine_age.jpg" />
</a>
</div>
<div class="half">
<blockquote>
I'm going to start worrying [...] the day my computer becomes aware of my printer."
</blockquote>
Andrew McAfee
</div>
</section>
<!-- This is something huge -->
<section data-background="img/scikit_learn.png">
<h1 style="color:black">Welcome to the jungle</h1>
</section>
<!-- Basics -->
<section>
<section>
<h2>How does it work?</h2>
<ul>
<li>Data in --> Model out</li>
<li>Model training and validation</li>
<li>Supervised vs. Unsupervised</li>
<li>Going live</li>
</ul>
</section>
<section>
<b>Data</b> in --> <b>Model</b> out
<img src="img/data2model.jpg" class="stretch" />
</section>
<section>
<b>Supervised</b> vs Unsupervised
<hr>
<table>
<tr>
<td colspan="4"><b>Features</b></td><td style="color:green;"><b>Target</b></td>
</tr>
<tr>
<td>Sex</td>
<td>Height</td>
<td>Weight</td>
<td>Age</td>
<td style="color:green;">Sport</td>
</tr>
<tr>
<td>M</td>
<td>1.67</td>
<td>60</td>
<td>20</td>
<td style="color:green;">soccer</td>
</tr>
<tr>
<td>F</td>
<td>1.95</td>
<td>90</td>
<td>28</td>
<td style="color:green;">basket</td>
</tr>
<tr>
<td>M</td>
<td>1.80</td>
<td>79</td>
<td>23</td>
<td style="color:green;">soccer</td>
</tr>
<tr>
<td>...</td>
<td>...</td>
<td>...</td>
<td>...</td>
<td>...</td>
</tr>
<tr>
<td>F</td>
<td>1.85</td>
<td>78</td>
<td>25</td>
<td><b style="color:red;">???</b></td>
</tr>
</table>
</section>
<section>
Supervised vs <b>Unsupervised</b>
<hr>
<table>
<td colspan="5"><b>Features</b></td>
<tr>
<td>Sex</td>
<td>Height</td>
<td>Weight</td>
<td>Age</td>
<td>Sport</td>
</tr>
<tr>
<td>M</td>
<td>1.67</td>
<td>60</td>
<td>20</td>
<td>soccer</td>
</tr>
<tr>
<td>F</td>
<td>1.95</td>
<td>90</td>
<td>28</td>
<td>basket</td>
</tr>
<tr>
<td>M</td>
<td>1.80</td>
<td>79</td>
<td>23</td>
<td>soccer</td>
</tr>
<tr>
<td>...</td>
<td>...</td>
<td>...</td>
<td>...</td>
<td>...</td>
</tr>
<tr>
<td><b style="color:red;">???</b></td>
<td><b style="color:red;">???</b></td>
<td><b style="color:red;">???</b></td>
<td><b style="color:red;">???</b></td>
<td><b style="color:red;">???</b></td>
</tr>
</table>
</section>
<section>
Training and <b>Validation</b>
<img src="img/model_validation.jpg" class="stretch" />
</section>
<section>
Training and <b>Validation</b>
<img src="img/confusion_matrix.png" class="stretch" />
</section>
<section>
<p><b>Going live</b></p>
<ul>
<li>You can train the model with a language...<br/>
(<b>python</b> wrappers of <b>C++</b> libs, running on a cluster)</li>
<li>... and use it with another!<br/>
(<b>Javascript</b> on mobile)</li>
<li>REST APIs, microservices</li>
</ul>
</section>
</section>
<!-- Deeper knowledge -->
<section data-background="#fff" class="white">
<section>
<h1>Inside the black box...</h1>
<ul>
<li>Linear algebra</li>
<li>Calculus</li>
<li>Probability</li>
</ul>
</section>
<section>
<h2>Linear algebra</h2>
<div>Vectors and matrices</div>
<div>
<span>
<a href="https://en.wikipedia.org/wiki/Linear_algebra">
<img height="300px" src="img/scatter_plot.svg" />
</a>
</span>
<span>
<a href="https://en.wikipedia.org/wiki/Linear_algebra">
<img height="300px" src="img/eigenvector.png" />
</a>
</span>
</div>
<small>It's all about points in space and their distance/transformation</small>
</section>
<section>
<h2>Calculus</h2>
<div>Derivatives, optimization</div>
<div>
<a href="https://upload.wikimedia.org/wikipedia/commons/1/1e/Extrema_example.svg">
<img height="400px" src="img/optimization.png" />
</a>
</div>
<small>It's all about changing parameters to minimize an error</small>
</section>
<section>
<h2>Probability</h2>
<div>Bayes</div>
<span>
<a href="https://en.wikipedia.org/wiki/Probability">
<img height="200px" src="img/probability_venn.png" />
</a>
</span>
<span>
<a href="https://en.wikipedia.org/wiki/Probability">
<img height="200px" src="img/bayes_rule.jpg" />
</a>
</span>
<small>It's all about confidence</small>
</section>
<section>
<h2>Don't be scared</h2>
<ul>
<li>It's just (a lot of) simple ideas</li>
<li>Math is just a compact representation</li>
</ul>
<div class="half">
<br/><br/>
\[\bar{x} = \frac{\sum_\limits{i=1}^{n} x_i}{n}\]
</div>
<div class="half">
<pre><code class="hljs" data-trim contenteditable>
function average(x) {
var n = x.length;
var sum = 0.0;
for(var i=0; i<n; i++){
sum += x[i];
}
return sum/n;
// TODO: don't divide by zero
}
</code></pre>
</div>
</section>
<section>
<h2>Don't be scared</h2>
<div class="half">
<table>
<tr>
<td>EYES</td>
<td>HAIR</td>
</tr>
<tr>
<td>green</td>
<td>red</td>
</tr>
<tr>
<td>green</td>
<td>black</td>
</tr>
<tr>
<td>black</td>
<td>black</td>
</tr>
<tr>
<td>green</td>
<td>red</td>
</tr>
</table>
</div>
<div class="half">
<br/><br/>
\[P(E_g|H_r) = \frac{P(E_g, H_r)}{P(H_r)}\]
</div>
<br clear="all"/>
<div>
<pre><code class="hljs php" data-trim contenteditable>
function conditional_probability($eyes="green", $hair="red"){
$prob_H =
sql("SELECT COUNT(*) FROM table WHERE HAIR=$hair");
$prob_E_and_H =
sql("SELECT COUNT(*) FROM table WHERE EYES=$eyes AND HAIR=$hair");
return $prob_E_and_H / $prob_H;
}
</code></pre>
</div>
</section>
</section>
<section>
<h1><a href="applications.html">Applications</a></h1>
</section>
</div>
</div>
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