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<!DOCTYPE html>
<html lang="en-us">
<head>
<meta charset="UTF-8">
<title>Intro to Data Science Fall 2018</title>
<meta name="viewport" content="width=device-width, initial-scale=1">
<link rel="stylesheet" type="text/css" href="stylesheets/normalize.css" media="screen">
<link href='https://fonts.googleapis.com/css?family=Open+Sans:400,700' rel='stylesheet' type='text/css'>
<link rel="stylesheet" type="text/css" href="stylesheets/stylesheet.css" media="screen">
<link rel="stylesheet" type="text/css" href="stylesheets/github-light.css" media="screen">
</head>
<body>
<section class="page-header">
<h1 class="project-name">Introduction to Data Science</h1>
<h2 class="project-tagline">Columbia University Science Honor Program Fall 2018</h2>
</section>
<section class="main-content">
<h3>
<a id="welcome-to-the-class!" class="anchor" href="#welcome-to-github-pages" aria-hidden="true"><span aria-hidden="true" class="octicon octicon-link"></span></a> <b>Welcome to The Class!</b></h3>
<p> In this class, we will explore theories in Probability, Statistics and Machine Learning, and apply them to solve real data problems using the programming language R. We will build the foundations from scratch --- no actual prerequisites required, but bring your curiosity! We will take your analytical skills to the next level. If you're simply seeking a challenge, we have something for you too! </p>
<p> Welcome and enjoy.
<h3>
<a id="calendar" class="anchor" href="#designer-templates" aria-hidden="true"><span aria-hidden="true" class="octicon octicon-link"></span></a><b>Calendar</b> (tentative)</h3>
<p> We will cover these major areas: regression, classification, clustering and data representation. </p>
<table class="fixed">
<col width="500px" />
<col width="2000px" />
<tr>
<th>Date</th>
<th>Contents</th>
</tr>
<tr>
<td>September 22</td>
<td>Math review. (LH)</td>
</tr>
<tr>
<td>September 29</td>
<td>Math review. Intro to R and RStudio. Naive Bayes Classifier. (LH)</td>
</tr>
<tr>
<td>October 6</td>
<td>Linear Classifiers. SVM. (LH)</td>
</tr>
<tr>
<td>October 13</td>
<td>Significance. (OW)</td>
</tr>
<tr>
<td>October 20</td>
<td>Regression. (OW)</td>
</tr>
<tr>
<td>October 27</td>
<td>Principal Component Analysis. (LH)</td>
</tr>
<tr>
<td>November 3</td>
<td>Nonparametric classification and regression. (LH)</td>
</tr>
<tr>
<td>November 10</td>
<td>LLT. CLT. Simulation. Monte Carlo integration. (OW)</td>
</tr>
<tr>
<td>November 17</td>
<td>Time Series. (OW)</td>
</tr>
<tr>
<td>December 1</td>
<td>Distributions as models. Optimization. (OW)</td>
</tr>
<tr>
<td>December 8</td>
<td>Text/Image analysis. (OW)</td>
</tr>
<tr>
<td>December 15</td>
<td>Neural Networks. (LH)</td>
</tr>
</table>
<h3>
<a id="lecture" class="anchor" href="#creating-pages-manually" aria-hidden="true"><span aria-hidden="true" class="octicon octicon-link"></span></a><b>Lecture</b></h3>
<p> <a href="lec1.html"> Lecture 1</a> </p>
<p> <a href="lec2.html"> Lecture 2</a> </p>
<p> <a href="lec3.html"> Lecture 3</a> </p>
<p> <a href="lec4.html"> Lecture 4</a> </p>
<p> <a href="lec5.html"> Lecture 5</a> </p>
<p> <a href="lec5.html"> Lecture 6</a> </p>
<p> <a href="lec8.html"> Lecture 8</a> </p>
<!--
<p> <a href="lec5.html"> Lecture 5</a> </p>
-->
<!--
<h3>
<a id="programming" class="anchor" href="#authors-and-contributors" aria-hidden="true"><span aria-hidden="true" class="octicon octicon-link"></span></a><b>Programming</b></h3>
<p> <b> Example 1:</b> <a href="example/naive_bayes2.R"> download</a> </p>
<p> <b> Example 2:</b> <a href="example/significance.R"> download</a> </p>
<p> <b> Example 3:</b> <a href="example/regression.R"> download</a> </p>
<p> <b> Example 4:</b> <a href="example/crime.R"> download</a> </p>
<p> <b> Example 5:</b> <a href="example/kmeans.R"> download</a> </p>
<p> <b> Example 6:</b> <a href="example/pca.R"> download</a> </p>
<p> <b> Example 7:</b> <a href="example/classification.R"> download</a> </p>
<p> <b> Example 8:</b> <a href="example/skyscrapers.R"> download</a> </p>
<p> <b> Example 3:</b> <a href="example/prediction.R"> download</a> </p>
<p> <a href="https://commercedataservice.github.io/tutorial_311_trees_p1/"> 311</a> </p>
<h3>
-->
<!-- <h3>
<a id="Election Prediction Project" class="anchor" href="#something-else" aria-hidden="true"><span aria-hidden="true" class="octicon octicon-link"></span></a><b>Project: 2016 Election Prediction</b></h3>
<p> <b>Data:</b> <a href="example/data_prediction.R"> download</a> </p>
<p> <b>Reference:</b> <a href="http://www.nytimes.com/interactive/2016/us/elections/polls.html?_r=1"> NYTimes</a>; <a href="http://elections.huffingtonpost.com/pollster/2016-general-election-trump-vs-clinton"> Huffpost</a>;
<a href="http://projects.fivethirtyeight.com/2016-election-forecast/national-polls/"> FiveThirtyEight</a>; <a href="http://www.gallup.com/poll/189299/presidential-election-2016-key-indicators.aspx?g_source=ELECTION_2016&g_medium=topic&g_campaign=tiles"> Gallup </a> </p>
<p> <b>Sample Code:</b> <a href="example/prediction.R"> download</a> </p>
<h3>
<h3>
<a id="challenges" class="anchor" href="#authors-and-contributors" aria-hidden="true"><span aria-hidden="true" class="octicon octicon-link"></span></a><b>Challenge Yourself</b></h3>
-->
<!--
<p> To submit your answer, please include all the derivation processes, either typed or hand-written. </p>
<p> <b> Milk or tea? </b> [<a href="q1.html"> Problem </a>] [<a href="mailto:yh2692@columbia.edu?subject=[SHP-DS-Fall2016] My answer to Q2"> Submit your answer! </a>] </p>
<p> <b> Regression through the origin </b> [<a href="q2.html"> Problem </a>] [<a href="mailto:yh2692@columbia.edu?subject=[SHP-DS-Fall2016] My answer to Q2"> Submit your answer! </a>] </p>
<p> <b> Fixed vs. Random Effects </b> [<a href="q3.html"> Problem </a>] [<a href="mailto:yh2692@columbia.edu?subject=[SHP-DS-Fall2016] My answer to Q3"> Submit your answer! </a>] </p>
<p> <b> Local Maximums </b> [<a href="q4.html"> Problem </a>] [<a href="mailto:yh2692@columbia.edu?subject=[SHP-DS-Fall2016] My answer to Q4"> Submit your answer! </a>] </p>
-->
<!--
<h3>
<p><a href="Crime.html">The crime example</a></p>
<p><a href="MonteCarlo.html">Monte Carlo estimation</a></p>
<p><a href="CLT.html">The Central Limit Theorem</a></p>
<p><a href="HMM.html">Hidden Markov Models</a></p>
-->
<h3>
<a id="resource" class="anchor" href="#designer-templates" aria-hidden="true"><span aria-hidden="true" class="octicon octicon-link"></span></a><b>Resources</b> </h3>
<p> https://forwards.github.io/edu/nyc/ </p>
</body>
</html>