Machine Learning Resources

An aggregation of resources for studying and keeping up to date with Machine Learning and mathematics.

Courses

• https://www.coursera.org/learn/machine-learning
• https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-034-artificial-intelligence-fall-2010/
• http://ai.berkeley.edu/home.html

Blogs and People

• http://www.paulgraham.com/
• https://jeremykun.com/
• https://opensource.googleblog.com/
• http://colah.github.io/
• http://cs.stanford.edu/people/karpathy/
  • http://karpathy.github.io/
• http://blog.stephenwolfram.com/
• https://developers.googleblog.com/

News & Aggregators

• http://technews.acm.org/
• https://news.ycombinator.com/
• https://www.kdnuggets.com
• https://www.nextplatform.com/category/analyze/
• https://twimlai.com/
• http://technews.acm.org/

Journals & Publications

• https://arxiv.org/
  • http://www.arxiv-sanity.com/
• https://distill.pub
• http://www.complex-systems.com
• https://fermatslibrary.com/

Books

• Artificial Intelligence: A Modern Approach - http://aima.cs.berkeley.edu/
• Computer Vision: Models, Learning, and Inference - http://www.computervisionmodels.com/
• Pattern Recognition and Machine Learning - https://www.microsoft.com/en-us/research/people/cmbishop/
• The Elements of Statistical Learning - https://web.stanford.edu/~hastie/ElemStatLearn/
• The Deep Learning Book - http://www.deeplearningbook.org/

Research Groups

• Cornell Machine Learning - http://machinelearning.cis.cornell.edu/index.php
• Oxford Information Engineering - http://www.robots.ox.ac.uk/
• Harvard Intelligent Probabilistic Systems - http://hips.seas.harvard.edu/
• MIT CS and AI - http://www.csail.mit.edu/

Conferences

• https://mlconf.com/
• https://nips.cc/

Videos

• The Great Danbury AI Playlist - https://www.youtube.com/playlist?list=PLXHD0TtFzS8s1sb14dRKAi5mRWFIl2G1Q

Platforms and Libraries

• Visualization
  • https://p5js.org/learn/
• Scientific Computing
  • https://www.scipy.org/
  • http://scikit-learn.org/
  • https://jupyter.org/
• NLP
  • https://github.com/explosion/spaCy
• TensorFlow
  • Boltzmann Machines in TensorFlow with examples - https://github.com/monsta-hd/boltzmann-machines
  • https://github.com/lengstrom/fast-style-transfer
  • https://github.com/vahidk/EffectiveTensorflow
  • https://github.com/jtoy/awesome-tensorflow

Code

• Deep Learning Book Study Group - https://github.com/DanburyAI/SG_DLB_2017