A course in Machine Learning.pdf


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Learning Methods Models incr 2810 fascinating broad Kernel 1169 Ensemble
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A Course in
Machine Learning
Hal Daumé III
Copyright © 2015 Hal Daumé III
Published by TODO
http://hal3.name/courseml/
TODO. . . .
First printing, September 2015
For my students and teachers.
Often the same.
TABLE OF CONTENTS
About this Book 6
1 Decision Trees 8
2 Geometry and Nearest Neighbors 26
3 The Perceptron 39
4 Practical Issues 53
5 Beyond Binary Classification 70
6 Linear Models 86
7 Probabilistic Modeling 103
8 Neural Networks 116
9 Kernel Methods 128
10 Learning Theory 141
5
11 Ensemble Methods 152
12 Efficient Learning 159
13 Unsupervised Learning 166
14 Expectation Maximization 175
15 Semi-Supervised Learning 181
16 Graphical Models 183
17 Online Learning 184
18 Structured Learning Tasks 186
19 Bayesian Learning 187
Code and Datasets 188
Notation 189
Bibliography 190
Index 191
ABOUT THIS BOOK
Machine learning is a broad and fascinating field. It has
been called one of the attractive fields to work in1. It has applications 1
in an incr


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