-
Notifications
You must be signed in to change notification settings - Fork 11
Expand file tree
/
Copy pathdata.php
More file actions
171 lines (159 loc) · 6.95 KB
/
data.php
File metadata and controls
171 lines (159 loc) · 6.95 KB
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
<?php
$reading_list = array (
"Linear Algebra" => array (
"Linear Algebra and Eigenproblems" => "downloads/Eigenproblems.fm.pdf",
),
"Support Vector Machines" => array (
"An ICML tutorial on SVMs" => "http://www.support-vector.net/icml-tutorial.pdf",
"Christopher Burges tutorial on SVMs for pattern recognition" => "http://research.microsoft.com/pubs/67119/svmtutorial.pdf",
"Scholkopf's NIPS tutorial slides on SVMs and kernel methods" => "downloads/svm-scholkopf.ps",
),
"Deep Learning" => array (
"Learning Deep Architectures for AI" => "downloads/learning_deep_architectures.pdf",
"Representation Learning" => "downloads/representation_learning.pdf",
),
"Boosting" => array (
"Schapire's Introduction" => "downloads/boosting.ps",
"Jiri Matas and Jan Sochman's Slides" => "downloads/adaboost_matas.pdf",
),
"Information Theory" => array (
"Charles Isbell's Note on Information Theory" => "downloads/InfoTheory.fm.pdf",
"An Introduction to Information Theory and Entropy" => "downloads/gentle_intro_to_information_theory.pdf",
),
"Optimization" => array (
"No Free Lunch Theoreom" => "downloads/nfl-optimization-explanation.pdf",
),
"Bayesian Inference" => array (
"Jon's notes on Bayesian Inference" => "downloads/bayesian_inference.pdf",
),
"Dimensionality Reduction" => array (
"ICA: Algorithms and Applications"=> "http://mlsp.cs.cmu.edu/courses/fall2012/lectures/ICA_Hyvarinen.pdf",
),
"Unsupervised Learning" => array (
"Intuitive Explanation of EM" => "http://www.cc.gatech.edu/~dellaert/em-paper.pdf",
"Stastical View of EM" => "downloads/em.pdf",
"Jon Kleinberg's Impossibility Theoreom for Clustering" => "http://machinelearning.wustl.edu/mlpapers/paper_files/LT17.pdf",
),
"Markov Decision Processes" => array (
"Jon's MDP Intro slides" => "downloads/MDPIntro.pdf",
"Richard Sutton and Andrew Barto, Reinforcement Learning: An introduction. MIT Press, 1998." => "http://webdocs.cs.ualberta.ca/~sutton/book/the-book.html",
"Reinforcement Learning: A Survey" => "downloads/kaelbling96reinforcement.pdf",
),
"Game Theory" => array (
"Andrew Moore's slides on Zero-Sum games" => "http://www.autonlab.org/tutorials/gametheory.html",
"Andrew Moore's slides on Non-zero-Sum games" => "http://www.autonlab.org/tutorials/nonzerosum.html",
),
);
$textbook_req_list = array (
"http://www.cs.cmu.edu/afs/cs.cmu.edu/user/mitchell/ftp/mlbook.html" => array (
"Tom Mitchell, Machine Learning. McGraw-Hill, 1997." => "",
),
"https://mitpress.mit.edu/books/introduction-machine-learning" => array (
"Ethem Alpaydın, Introduction to Machine Learning. Second Edition." => "",
)
);
$textbook_opt_list = array (
"http://www.stat.cmu.edu/~larry/all-of-statistics/" => array (
"Larry Wasserman, All of Statistics. Springer, 2010." => "",
),
"http://webdocs.cs.ualberta.ca/~sutton/book/the-book.html" => array (
"Richard Sutton and Andrew Barto, Reinforcement Learning: An introduction. MIT Press, 1998." => "",
),
"http://www-stat.stanford.edu/~tibs/ElemStatLearn/" => array (
"Trevor Hastie, Robert Tibshirani and Jerome Friedman, The Elements of Statistical Learning. Springer, 2009." => "",
)
);
$software_list = array (
"http://www.cs.waikato.ac.nz/ml/weka/" => array (
"WEKA" => "Machine learning software in JAVA that you can use for your projects",
),
"https://weka.waikato.ac.nz/" => array (
"Data Mining with Weka" => "A MOOC Course",
),
"https://github.com/pushkar/ABAGAIL" => array (
"ABAGAIL" => "Machine learning software in JAVA. This is hosted on my github, so you can contribute too",
),
"http://scikit-learn.org/stable/" => array (
"scikit-learn" => "A popular python library for supervised and unsupervised learning algorithms",
),
"http://pybrain.org/" => array (
"pybrain" => "A popular python library for artifical neural networks",
),
"http://www.mathworks.com/products/neural-network/examples.html" => array (
"MATLAB NN Toolbox" => "The toolbox supports supervised learning with feedforward, radial basis, and dynamic networks and unsupervised learning with self-organizing maps and competitive layers.",
),
"http://www.cs.ubc.ca/~murphyk/Software/MDP/mdp.html" => array (
"Murphy's MDP Toolbox for Matlab" => "",
),
"http://www.cc.gatech.edu/~dellaert/FrankDellaert/Software.html" => array (
"MATLAB Clustering Package" => "By <a href=\"http://www.cc.gatech.edu/~dellaert/FrankDellaert/Frank_Dellaert/Frank_Dellaert.html\">Frank Dellaert</a>",
),
"http://www.robotvisions.org/4641/downloads/ica.tar.gz" => array (
"ICA Example" => "",
),
);
$app_list = array (
"http://www.youtube.com/watch?v=jQXPy9rsaAA" => array (
"Robosoccer." => "",
),
"http://make3d.cs.cornell.edu/" => array (
"Make3D - Convert your still image into 3D model." => "",
),
"http://heli.stanford.edu/" => array (
"Autonomous Helicopter." => "",
),
"http://www.youtube.com/watch?v=SH3bADiB7uQ" => array (
"Learning to play ping pong." => "",
),
"http://research.ics.aalto.fi/ica/cocktail/cocktail_en.cgi" => array (
"Cocktail Party Demo." => "",
),
"http://www.youtube.com/watch?v=DleXA5ADG78" => array (
"Brains, Sex, and Machine Learning" => "Geoffrey Hinton <a href=\"http://yann.lecun.com/ex/fun/\">(facts)</a> in GoogleTechTalks.",
),
"http://www.youtube.com/watch?v=3liCbRZPrZA" => array (
"SVM with polynomial kernel visualization" => "Example from class",
)
);
$other_list = array (
"http://archive.ics.uci.edu/ml/" => array (
"UCI Machine Learning Repository" => "An online repository of data sets that can be used for machine learning experiments.",
),
"http://snap.stanford.edu/data/" => array (
"Stanford Large Network Dataset" => "Dataset of large social and information networks.",
),
"http://www.cvlibs.net/datasets/kitti/index.php" => array (
"Vision Benchmark Suite" => "Autonomous car dataset",
),
"http://kevinchai.net/datasets" => array (
"Other datasets" => "",
)
);
function list_reading($arr) {
echo "<ul>";
foreach ($arr as $topic => $topic_list) {
echo "<li>";
echo "$topic";
echo "<ul>";
foreach ($topic_list as $heading => $url) {
echo "<li>";
echo "<a href=\"$url\">$heading</a>";
echo "</li>";
}
echo "</ul>";
echo "</li>";
}
echo "</ul>";
}
function list_other($arr) {
echo "<ul>";
foreach ($arr as $url => $info) {
echo "<li>";
foreach ($info as $url_info => $more_info) {
echo "<a href=\"$url\">$url_info</a> $more_info";
}
echo "</li>";
}
echo "</ul>";
}
?>