DanburyAI / MachineLearningResources

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

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