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# Title Author Topic Medium Score
1 Bertrand and Russell Ben King 362 naclo 4.34
2 Evaluation Dan Roth 451 lecture 4.33
3 LSTMs for Human Activity Recognition Guillaume Chevalier 742 library 4.32
4 The Confusion Matrix in statistical tests Eli Bendersky 974 resource 4.30
5 Cross-validation for detecting and preventing overfitting Andrew W. Moore 107 tutorial 4.30
6 Introduction to Bayesian Thinking: from Bayes Theorem to Bayes Networks Felipe Sanchez 171 resource 4.29
7 Machine Learning with scikitlearn Sebastian Raschka, Andreas Mueller 134 tutorial 4.29
8 Two-sample t-test and robustness John Cook 999 resource 4.29
9 Intro to Data Science Part 3: Data Analysis Tiffany Souterre 974 resource 4.29
10 Information Retrieval 8 David Smith 61 lecture 4.28
11 Multi Label Text Classification with Scikit-Learn Susan Li 542 resource 4.28
12 Multi Label Text Classification with Scikit-Learn Susan Li 542 resource 4.28
13 Features and hypothesis tests David Bamman 543 lecture 4.28
14 factorie-nlp-scripts Emma Strubell 251 library 4.27
15 An Introduction to Machine Learning in Python Sebastian Raschka 134 tutorial 4.27
16 Minibatch Metropolis-Hastings Daniel Seita 107 tutorial 4.27
17 A Corpus and Cloze Evaluation for Deeper Understanding of Commonsense Stories Nasrin Mostafazadeh, Nathanael Chambers, Xiaodong He, Devi Parikh, ... 999 paper 4.27
18 The 6th Open Challenge on Question Answering Over Linked Data Christina Unger 755 corpus 4.27
19 30 Questions to test a data scientist on Natural Language Processing [Solution: Skilltest – NLP] Shivam Bansal 112 resource 4.26
20 Statistics Tutorial Harvey Berman 102 tutorial 4.26
21 Prepositional Phrase Attachment 3 Dragomir Radev 284 lecture 4.26
22 Prepositional Phrase Attachment 3 Dragomir Radev 284 lecture 4.25
23 Nuts and bolts of building AI applications using Deep Learning Andrew Ng 811 tutorial 4.25
24 Experimentation Chris Dyer 107 lecture 4.25
25 Cornell Natural Language Visual Reasoning (NLVR) Alane Suhr, Mike Lewis, James Yeh, and Yoav Artzi library 4.25
26 Story Cloze Test and ROCStories Corpora Author Unknown 979 corpus 4.25
27 cs231n notes: Classification Andrej Karpathy 511 tutorial 4.25
28 Tutorial on Universal Dependencies: CoNLL shared task on UD parsing Joakim Nivre, Daniel Zeman, Filip Ginter, Francis M. Tyers 258 tutorial 4.25
29 How to Unit Test Machine Learning Code Chase Roberts 731 tutorial 4.24
30 LF-LDA and LF-DMM: Improving Topic Models with Word Embeddings Dat Quoc Nguyen, Richard Billingsley, Lan Du and Mark Johnson 721 library 4.24
31 Exploring and Denoising Your Data Set Terence Parr, Jeremy Howard 112 resource 4.24
32 dimensionality reduction technique -tsne vs. PCA Zenodia Charpy 341 tutorial 4.24
33 Confidence Intervals and Hypothesis Testing Roger Levy tutorial 4.24
34 Supervised Learning Methods k-nearest-neighbors(k-NN) Decisiontrees(Chapter18.3) Neuralnetworks(ANN) Supportvectormachines(SVM) Chuck Dyer 511 lecture 4.24
35 Design and Analysis of Machine Learning Experiments Ethem Alpaydın 134 lecture 4.23
36 Naive Bayes and Sentiment Classification Daniel Jurafsky, James H. Martin 381 survey 4.23
37 Practical Considerations of Classification Dragomir Radev 545 lecture 4.22
38 Solving A Simple Classification Problem with Python - Fruits Lovers's Edition Susan Li 381 resource 4.22
39 How (and why) to create a good validation set Rachel Thomas tutorial 4.22
40 Just Machine Learning Tina Eliassi-Rad 134 tutorial 4.22
41 Tensor Comprehensions Nicolas Vasilache, Priyal Goyal 731 resource 4.22
42 L1 regularization & Intro to learning theory David Sontag 107 lecture 4.22
43 Build It, Break It The Language Edition Emily M. Bender, Hal Daume III, Allyson Ettinger, Harita Kannan, Su... 133 corpus 4.21
44 Comprehension Based LanguageÿModeling David McAllester 211 resource 4.21
45 Prepositional Phrase Attachment 1 Dragomir Radev 282 lecture 4.21
46 Practical Considerations of Classification Dragomir Radev 545 lecture 4.21
47 Lecture 1: Introduction Kevin Gimpel 31 lecture 4.21
48 Tutorial on Ensemble Learning Igor Baskin, Gilles Marcou and Alexandre Varnek 107 survey 4.20
49 Machine learning III Percy Liang 134 lecture 4.20
50 Basics of Bayesian Statistics Author Unknown 134 survey 4.20