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2013-03-15-Review.html
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2013-03-15-Review.html
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<?xml version="1.0" encoding="utf-8"?>
<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Strict//EN"
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<html xmlns="http://www.w3.org/1999/xhtml" lang="en" xml:lang="en">
<head>
<title>2013-03-14-Review</title>
<meta http-equiv="Content-Type" content="text/html;charset=utf-8"/>
<meta name="title" content="2013-03-14-Review"/>
<meta name="generator" content="Org-mode"/>
<meta name="generated" content="2013-03-15 13:36:52 PDT"/>
<meta name="author" content="Jim Blomo"/>
<meta name="description" content=""/>
<meta name="keywords" content=""/>
<link rel="stylesheet" type="text/css" href="production/common.css" />
<link rel="stylesheet" type="text/css" href="production/screen.css" media="screen" />
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<link rel="stylesheet" type="text/css" href="production/presenter.css" media="presenter" />
<link href='http://fonts.googleapis.com/css?family=Lobster+Two:700|Yanone+Kaffeesatz:700|Open+Sans' rel='stylesheet' type='text/css'>
</head>
<body>
<div id="preamble">
</div>
<div id="content">
<h1 class="title">2013-03-14-Review</h1>
<div id="table-of-contents">
<h2>Table of Contents</h2>
<div id="text-table-of-contents">
<ul>
<li><a href="#sec-1">1 Review</a></li>
<li><a href="#sec-2">2 Case Studies</a></li>
<li><a href="#sec-3">3 Obtaining Data</a></li>
<li><a href="#sec-4">4 Probability</a></li>
<li><a href="#sec-5">5 Preprocessing</a></li>
<li><a href="#sec-6">6 Data Warehouse</a></li>
<li><a href="#sec-7">7 MapReduce</a></li>
<li><a href="#sec-8">8 Decision Tree</a></li>
<li><a href="#sec-9">9 Naive Bays</a></li>
<li><a href="#sec-10">10 SVM</a></li>
<li><a href="#sec-11">11 Neural Networks</a></li>
<li><a href="#sec-12">12 Partitioning Clusters</a></li>
<li><a href="#sec-13">13 Hierarchical Clustering</a></li>
<li><a href="#sec-14">14 <b>Good Luck!</b></a></li>
</ul>
</div>
</div>
<div id="outline-container-1" class="outline-2">
<h2 id="sec-1"><span class="section-number-2">1</span> Review <span class="tag"><span class="slide">slide</span></span></h2>
<div class="outline-text-2" id="text-1">
<ul>
<li>Midterm target length: 1.5 hours
</li>
<li>Time limit: 3 hours
</li>
<li>1 cheat sheet, 8.5x11
</li>
<li>Calculators OK, not required
</li>
<li>Questions from slides have a higher probability of appearing
</li>
<li>Questions from the reading are fair game
</li>
</ul>
</div>
</div>
<div id="outline-container-2" class="outline-2">
<h2 id="sec-2"><span class="section-number-2">2</span> Case Studies <span class="tag"><span class="slide">slide</span></span></h2>
<div class="outline-text-2" id="text-2">
<ul>
<li>Example of "transactional data"
</li>
<li>Example of non-transactional data
</li>
</ul>
</div>
</div>
<div id="outline-container-3" class="outline-2">
<h2 id="sec-3"><span class="section-number-2">3</span> Obtaining Data <span class="tag"><span class="slide">slide</span></span></h2>
<div class="outline-text-2" id="text-3">
<ul>
<li>Tradeoffs of dataset vs API?
</li>
<li>Tradeoffs of operational database vs data warehouse
</li>
<li>Unix commands to explore data?
</li>
</ul>
</div>
</div>
<div id="outline-container-4" class="outline-2">
<h2 id="sec-4"><span class="section-number-2">4</span> Probability <span class="tag"><span class="slide">slide</span></span></h2>
<div class="outline-text-2" id="text-4">
<ul>
<li>Other names for a Feature
</li>
<li>Difference between Discrete and Continuous feature
</li>
<li>What type of feature is day of the week?
</li>
<li>Ways to measure central tendency?
</li>
<li>What is skew?
</li>
<li>When is asymmetric binary dissimilarity useful?
</li>
<li>How to calculate L<sub>2</sub> norm of two points?
</li>
<li>What is cosign similarity?
</li>
</ul>
</div>
</div>
<div id="outline-container-5" class="outline-2">
<h2 id="sec-5"><span class="section-number-2">5</span> Preprocessing <span class="tag"><span class="slide">slide</span></span></h2>
<div class="outline-text-2" id="text-5">
<ul>
<li>When storing the same fact in different ways, what type of problem is
likely?
</li>
<li>Can data corruption happen with no mistakes and no bugs?
</li>
<li>What are some options to deal with missing values?
</li>
<li>What are some options to deal with outliers?
</li>
<li>What does correlation imply?
</li>
</ul>
</div>
</div>
<div id="outline-container-6" class="outline-2">
<h2 id="sec-6"><span class="section-number-2">6</span> Data Warehouse <span class="tag"><span class="slide">slide</span></span></h2>
<div class="outline-text-2" id="text-6">
<ul>
<li>OLAP vs OLTP
</li>
<li>Examples of database metadata?
</li>
<li>What is a data multi-cube?
</li>
<li>What is at the center of a star schema?
</li>
<li>What is the tradeoff being made in dimension tables?
</li>
<li>Define:
<ul>
<li>Rollup
</li>
<li>Drill-down
</li>
<li>Slice
</li>
<li>Dice
</li>
<li>Pivot
</li>
</ul>
</li>
</ul>
</div>
</div>
<div id="outline-container-7" class="outline-2">
<h2 id="sec-7"><span class="section-number-2">7</span> MapReduce <span class="tag"><span class="slide">slide</span></span></h2>
<div class="outline-text-2" id="text-7">
<ul>
<li>What tradeoff are we making with MapReduce?
</li>
<li>Why is log processing a typical use of MapReduce?
</li>
<li>What types of processing is not well suited?
</li>
<li>For a multi-step job, the output of a reducer is fed into what?
</li>
</ul>
</div>
</div>
<div id="outline-container-8" class="outline-2">
<h2 id="sec-8"><span class="section-number-2">8</span> Decision Tree <span class="tag"><span class="slide">slide</span></span></h2>
<div class="outline-text-2" id="text-8">
<ul>
<li>What table can we create from the verification results to understand
performance of our model?
</li>
<li>For supervised learning, what is required to train a model?
</li>
<li>What is a naive way to optimize precision?
</li>
<li>Recall?
</li>
<li>Assuming we use all attributes to classify, what is the height of
our tree?
</li>
<li>What are we optimizing for in the leaf nodes?
</li>
</ul>
</div>
</div>
<div id="outline-container-9" class="outline-2">
<h2 id="sec-9"><span class="section-number-2">9</span> Naive Bays <span class="tag"><span class="slide">slide</span></span></h2>
<div class="outline-text-2" id="text-9">
<ul>
<li>Where does the testing set come from?
</li>
<li>What is the <code>k</code> in k-fold cross-validation?
</li>
<li>Bayes theorem finds P(A|B). In email spam detection, what are A and B?
</li>
<li>What is the Naive assumption we make in Naive Bayes?
</li>
<li>Why can training many models be useful?
</li>
<li>What is bootstrap sampling?
</li>
<li>What is a random forest?
</li>
</ul>
</div>
</div>
<div id="outline-container-10" class="outline-2">
<h2 id="sec-10"><span class="section-number-2">10</span> SVM <span class="tag"><span class="slide">slide</span></span></h2>
<div class="outline-text-2" id="text-10">
<ul>
<li>When finding a linear fit for home prices, what is our fitness function?
</li>
<li>What is the gradient in gradient descent?
</li>
<li>In the general case, are you guaranteed to find the globally optimal
solution when using gradient descent?
</li>
<li>Why does SVM work so well in practice, even though it requires linear
separability?
</li>
<li>If your data is not linearly separable, can you use SVM?
</li>
</ul>
</div>
</div>
<div id="outline-container-11" class="outline-2">
<h2 id="sec-11"><span class="section-number-2">11</span> Neural Networks <span class="tag"><span class="slide">slide</span></span></h2>
<div class="outline-text-2" id="text-11">
<ul>
<li>What is model variance?
</li>
<li>What problem does high model variance indicate?
</li>
<li>What is an activation function?
</li>
<li>What types of problems are neural networks especially suited for?
</li>
<li>What are we improve during backward propagation?
</li>
</ul>
</div>
</div>
<div id="outline-container-12" class="outline-2">
<h2 id="sec-12"><span class="section-number-2">12</span> Partitioning Clusters <span class="tag"><span class="slide">slide</span></span></h2>
<div class="outline-text-2" id="text-12">
<ul>
<li>What is the difference between k-means and k-nearest-neighbor?
</li>
<li>What are some of the problems with k-means?
</li>
<li>Why is normalization especially useful in clustering?
</li>
<li>What are the tradeoffs for using k-medoid clustering?
</li>
</ul>
</div>
</div>
<div id="outline-container-13" class="outline-2">
<h2 id="sec-13"><span class="section-number-2">13</span> Hierarchical Clustering <span class="tag"><span class="slide">slide</span></span></h2>
<div class="outline-text-2" id="text-13">
<ul>
<li>What are the options to calculate cluster distance?
</li>
<li>Describe how to draw a dendrogram
</li>
<li>What are the drawbacks to density clustering with DBSCAN?
</li>
<li>If you had movie description data, but no genres, would you use Fuzzy
Clustering or Partitioned Clustering?
</li>
<li>How can we evaluate a clustering algorithm if our data is already labeled
with clusters?
</li>
</ul>
</div>
</div>
<div id="outline-container-14" class="outline-2">
<h2 id="sec-14"><span class="section-number-2">14</span> <b>Good Luck!</b> <span class="tag"><span class="slide">slide</span></span></h2>
<div class="outline-text-2" id="text-14">
<script type="text/javascript" src="production/org-html-slideshow.js"></script>
</div>
</div>
</div>
<div id="postamble">
<p class="date">Date: 2013-03-15 13:36:52 PDT</p>
<p class="author">Author: Jim Blomo</p>
<p class="creator">Org version 7.8.02 with Emacs version 23</p>
<a href="http://validator.w3.org/check?uri=referer">Validate XHTML 1.0</a>
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