Here you’ll find links to useful resources on machine learning.
Institution | Instructor | Name of the course | Code |
---|---|---|---|
Caltech (California Institute of Technology) | Yaser S. Abu-Mostafa | Learning from Data | |
Stanford | Andrew Ng | Machine Learning | |
Stanford | Andrew Ng | Unsupervised Feature Learning and Deep Learning | |
Carnegie Mellon University | Tom Mitchell | Machine Learning | |
Coursera/Stanford | Andrew Ng | Machine Learning | |
Edx/Berkeley | Ameet Talwalkar | Scalable Machine Learning | |
Udacity | Sebastian Thrun/Katie Malone | Intro to Machine Learning | |
Udacity/GeorgiaTech | Michael Littman/Charles Isbell | Machine Learning | |
Data School | Kevin Markham | Introduction to machine learning with scikit-learn | |
Udacity | Sebastian Thrun | Intro to Statistics | st101 |
Stanford | Richard Socher | Deep Learning for Natural Language Processing | cs224d |
Researcher/Team | Web address |
---|---|
Andrew Ng | http://cs.stanford.edu/people/ang/ |
Adam Coates | http://www.cs.stanford.edu/~acoates/ |
Sierra Research Team | http://www.di.ens.fr/sierra/ |
Yann LeCun | http://yann.lecun.com/ |
Michael Littman | http://cs.brown.edu/~mlittman/ |
Charles Isbell | http://www.cc.gatech.edu/~isbell/ |
Software name | Notes |
---|---|
Matlab | |
Gnu Octave | |
Gnu Plot |
Library name | Notes |
---|---|
LIBSVM | |
LIBLINEAR | |
Math.Net |
What is in it? | Notes |
---|---|
Stanford CS229 | |
Stanford CS294a | |
Meachine Learning courses on CosmoLearning | |
Deep Learning courses by Andrew Ng | |
Read the Web | |
Adam Coates and Andrew Ng on Reddit |
Journal name | Notes |
---|---|
Gaussian Process |
Main subject | Title | Notes |
---|---|---|
K-NN algorithm | Discriminatory Analysis | unpublished technical report |
Spark | Spark: Cluster Computing with Working Sets | |
Spark | Resilient Distributed Datasets: A Fault-Tolerant Abstraction for In-Memory Cluster Computing | |
Spark - MLlib | MLlib: Machine Learning in Apache Spark |
Article name | Notes |
---|---|
Simpson’s Paradox | |
Deep learning weekly |
Data | Notes |
---|---|
MatrixMarket | |
Machine Learning Repository | |
the MNIST database of handwritten digit | |
MovieLens | |
Dataset gathered by Michael Stob | There are several data sets that can be of interest to test algorithms, includes also UC Berkeley Admissions data (Simpson’s Paradox data) |
Last.fm Web Services |
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