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---
layout: page
title: Home
weight: 0
---
<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="utf-8">
<meta http-equiv="X-UA-Compatible" content="IE=edge">
<meta name="viewport" content="width=device-width, initial-scale=1">
<!-- The above 3 meta tags *must* come first in the head; any other head content must come *after* these tags -->
<meta name="description" content="">
<meta name="author" content="">
<link rel="icon" href="../../favicon.ico">
<script src="https://ajax.googleapis.com/ajax/libs/jquery/1.12.0/jquery.min.js"></script>
<script src="jquery.dataTables.min.js"></script>
<script src="bib-list.js"></script>
<link rel="stylesheet" href="bib-publication-list.css" type="text/css" />
<title>Harvard CS 181</title>
<!-- Bootstrap core CSS -->
<link rel="stylesheet" href="//netdna.bootstrapcdn.com/bootstrap/3.3.5/css/bootstrap.min.css">
<script src="https://maxcdn.bootstrapcdn.com/bootstrap/3.3.5/js/bootstrap.min.js"></script>
<link rel="stylesheet" href="page.css">
</head>
<body>
<div class="row">
</div>
<div class="container">
<div class="panel panel-primary" style="margin-top:10px;background-color:purple;border-color:#000000;">
<div class="panel-heading" style="background-color:plum;border-color:#2D6ED3;">
<h1>CS181: Machine Learning</h1>
<p class="lead">Finale Doshi-Velez, Harvard University</p>
</div>
<div class="panel-footer">
<ul class="nav nav-tabs invert-colors">
<li class="active"><a data-toggle="tab" href="#home_tab">Home</a></li>
<li><a data-toggle="tab" href="#schedule_tab">Schedule</a></li>
<li><a data-toggle="tab" href="#people_tab">People</a></li>
<li><a data-toggle="tab" href="#camelot_tab">Camelot.ai</a></li>
</ul>
</div>
</div>
<div class="container">
<div class="tab-content">
<div id="home_tab" class="row tab-pane fade in active">
<div class="row container">
<p><span style="font-size: 1.17em;font-weight: bold;">Time:</span> Mon/Wed 9:00-10:30am</p>
<p><span style="font-size: 1.17em;font-weight: bold;">Location:</span> Northwest Building B103 </p>
</div>
<div class="row container">
<h3 id="announcements_description">Announcements (check piazza too)</h3>
<div class="container ">
<!-- <div class="panel-body"> -->
<ul>
<li> Midterm 1 in class on Monday 3/5.
No section during the preceding week (2/26, 2/27, 2/28).
Two midterm review sessions:
4:30-5:30pm on Friday 3/2 in Science Center B and
2-3pm on Saturday 3/3 in Science Center E.
Review topics and questions in the section repo.</li>
<li> Meet the Staff Pizza Party (with CS 124) on Friday, January 26th 1-2:15pm in MD ground floor lobby! Come to
ask general questions about the course, meet homework partners, and eat pizza! </li>
<li> Section 0 Math Review sessions on <b>Sunday, January 21st at 4pm in Pierce 301 and Tuesday,
January 23rd at 5pm, MD 1st floor lobby
(one floor above ground floor)</b>.
These will not *teach* but will *briefly review* topics in Linear Algebra, Multivariate Calculus,
and Probability Theory. For Sunday, if you cannot get into Pierce, try going through the guard
at Maxwell Dworkin or email Mark (find email linked on the people tab of this website).
Note: these are not the regular section times. </li>
</ul>
</div>
</div>
<div class="row container">
<h3 id="description">Course Info</h3>
<div class="container ">
<!-- <div class="panel-body"> -->
<dl>
<dt>Forum and Announcements</dt>
<dd><ul>
<li><a href="https://piazza.com/harvard/spring2018/cs181/">Piazza </a> </li>
</ul></dd>
<dt>Section Times </dt>
<dd>
Regular section times:
<ul>
<li>Monday 4-5pm, 5-6:30pm (extended): Pierce 301 (except 2/26)</li>
<li>Tuesday 4-5:30pm (extended): Science Center 309a</li>
<li>Wednesday 4-5pm, 5-6pm: MD119</li>
</ul>
</dd>
<dt>Office Hours (starting Thursday 1/25)</dt>
<dd>
<ul>
<li> Finale's OH: Wednesday 3-4:30pm in MD 219 (smaller than other OH)</li>
{% for oh in site.data.all.ohs %}
<li>{{oh.time}}: {{oh.location}}</li>
{% endfor %}
</ul>
</dd>
<dt>Syllabus and Collaboration Policy</dt>
<dd>
<ul>
<li>See the course <a href="syllabus.pdf">syllabus</a>
</ul>
</dd>
<dt>Links</dt>
<dd>
<ul>
<li><a href="https://canvas.harvard.edu/courses/37343">Canvas Site</a></li>
<li><a href="https://docs.google.com/forms/d/e/1FAIpQLSftYPFRFqxuTLxZiDy7RSHxhPU1aeRStHdJpnHzcPaa3pzbnQ/viewform?usp=sf_link">Special Registration Form</a> if you need help registering for this course </li>
<li><a href="https://github.com/harvard-ml-courses/cs181-lectures">Lecture Notes Repo</a> (Finale's lecture notes in s18/ and last year's slides in s17/) </li>
<li><a href="https://github.com/harvard-ml-courses/cs181-section">Section Repo</a></li>
<li><a href="https://github.com/harvard-ml-courses/cs181-demos">Demo Repo</a></li>
<li><a href="https://github.com/harvard-ml-courses/cs181-s18-homeworks">Homework Repo</a> (seed repo to pull from using GitHub Classroom repo) </li>
<li><a href="https://github.com/harvard-ml-courses/cs181-s18-practicals">Practical Repo</a> (seed repo to pull from using GitHub Classroom repo) </li>
<li><a href="https://classroom.github.com/a/tXtSHNcl">Create GitHub Classroom for homeworks</a> (make a homework repo just once)</li>
</ul>
</dd>
<dt>References</dt>
<dd><ul>
<li> Bishop 2006, <a href="http://www.springer.com/us/book/9780387310732">Pattern Recognition and Machine Learning</a> (required text)</li>
<li> Murphy 2012, <a href="http://harvardcoopbooks.bncollege.com/webapp/wcs/stores/servlet/BNCB_TextbookDetailView?catalogId=10001&item=N&langId=-1&productId=600005699137&storeId=52084">Machine Learning: A Probabilistic Perspective</a> (optional readings)
<li> Petersen and Pedersen 2012, <a href="http://www2.imm.dtu.dk/pubdb/views/edoc_download.php/3274/pdf/imm3274.pdf">The Matrix Cookbook</a>
</ul></dd>
<dt>Grading</dt>
<dd>
<ul>
<li> 5 Theory Homeworks (30%) </li>
<li> 4 Practicals (30%) </li>
<li> 2 Midterms (40%) </li>
</ul>
</dd>
<dt>Other Courses</dt>
<dd>
<ul>
<li><a href="https://harvard-ml-courses.github.io/cs181-web-2017/">CS181 Spring 2017</a> (has lecture slides, section notes, etc...) </li>
<li><a href="https://harvard-ml-courses.github.io/cs281-web/">CS281 Fall 2017</a> (Advanced Machine Learning) </li>
<li><a href="https://people.seas.harvard.edu/~yaron/teaching.html">CS282 Spring 2018</a> (Robust Machine Learning) </li>
<li><a href="https://harvard-ml-courses.github.io/cs287-web/">CS287 Spring 2018</a> (Machine Learning for Natural Language) </li>
</ul>
</dd>
</dl>
</div>
</div>
</div>
<div id="people_tab" class="row tab-pane fade">
<div class="row container">
<dl>
<dt>Instructor</dt>
<dd> <ul>
<li>Finale Doshi-Velez </li>
<li>Email: Piazza preferred or finale at seas.harvard.edu </li>
</ul>
</dd>
<dt>Teaching Fellows</dt>
<dd>
<ul>
{% for ta in site.data.all.tas %}
<li> {{ta.name}} </li>
{% endfor %}
</ul>
</dd>
<dt> ethiCS: </dt>
<dd>
<ul>
<li> <a href="mailto:[email protected]">Kate Vredenburgh</a> </li>
</ul>
</dd>
<dt> Contact for exceptional circumstances: </dt>
<dd>
<ul>
<li> <a href="mailto:[email protected]">Osvaldo Galeano</a> </li>
</ul>
</dd>
<dt> Educational Technology </dt>
<dd>
<ul>
<li> Gabe Abrams </li>
<li> <a href="mailto:[email protected]">Canvas Support</a> </li>
</ul>
</dd>
</dl>
</div>
</div>
<div id="schedule_tab" class="row tab-pane fade">
<div class="row container">
<div class="tab-content">
<table class="table">
<tr><th>Date</th> <th>Topic</th> <th>Subtopic</th> <th>Section</th> <th>Demos </th><th>Readings</th><th>Assignment </th></tr>
{% for lecture in site.data.all.lectures %}
<tr id = {{lecture.type|default("",true)}}>
<td> {{site.data.all.dates[forloop.index]}} </td>
<td> {{lecture.topic | default("",true)}} </td>
<td> {{lecture.subtopic|default("", true)}}</td>
<td> {{lecture.section|default("", true)}}</td>
<td> {{lecture.demos|default("", true)}}</td>
<td> {{lecture.readings|default("", true)}}</td>
<td> {{lecture.hw | default("",true)}}</td>
</tr>
{% endfor %}
</table>
</div>
</div>
</div>
<div id="camelot_tab" class="row tab-pane fade">
<div class="row container" id="camelot-container">
<a href="https://camelot.ai/" target="_blank">
<img src="https://d2mxuefqeaa7sj.cloudfront.net/s_F38EEFEE5E13188081B7FE195E76A90CD0A2D4F689B3D6E36861D18C4CF27896_1517280633605_camelot_banner.png" width="100%"/>
</a>
<br />
<br />
<div id="camelot-text">
<p>
<a href="https://camelot.ai" target="_blank">Camelot.ai</a> is an online platform for machine learning problem-solving and skills development built by three former CS181 students. We focus on helping you learn real, practical skills and using our data to match your talent with top quantitative/technical companies. CS181 uses Camelot.ai for the practicals.
</p>
<p>
Machine learning & data science are only getting bigger, and it’s not enough to just be able to code up a simple BFS algorithm in your next tech interview. Our problems have varying difficulties and are designed to mimic real, fun projects, with multiple steps building on one other.
</p>
<p>
Enter the <a href="https://portal.camelot.ai/arena" target="_blank">Arena</a> to register for one of our weekly tournaments — done right in the browser — with prizes for everyone who finishes (like American Apparel Tshirts!), and additional rewards for top winners. Students who consistently do well will be referred to our sponsoring firms. Itching to get started? Check out the <a href="https://portal.camelot.ai/vault" target="_blank">Vault</a> to try your hand at some past tournament problems!
</p>
<p>
<b>How are you different from Kaggle?</b><br />
First, our problems are designed to be more engaging and interactive, in contrast to simply generating predictions on a giant data set. We tie problems to specific techniques or technologies. Second, Kaggle is not very accessible. Very few people outside of the top 1000 data scientists in the world (+ lots of time and resources) have a shot at winning a Kaggle competition. Our is aim is for users to solve fun, challenging problems and learn at the same time.
</p>
<p>
<b>Can we give feedback on the product?</b><br />
Yes definitely! Shoot a message to <a href="mailto:[email protected]">[email protected]</a> or talk to us directly through the chat box in the portal.
</p>
</div>
</div>
</div>
</div>
</div> <!-- /container -->
</body>
</html>
<head>
</head>
<html>
</html>