Machine Learning

Resources

Blog/Webpage

• deeplearning.net
• Joseph Misti's Curated List of ML software
• Google Brain AMA
• Training Tips and Tricks
• Denny Britz's wildml blog
• Written Memories: Understanding, Deriving and Extending the LSTM
• Colah's ML tutorials
• Andrej Karpathy's blog
• Awesome Deep Learning Papers
• Andrew Ng Quora QA

Video Lectures

• Deep Learning Summer School (Montreal 2015)
• Deep Learning Summer School (Montreal 2016)
• Deep Learning (2009 Hinton)
• Variational Autoencoder (2015 Courville)
• Deep Belief Networks (Hinton 2009)
• Deep Learning with Multiplicative Interactions (Hinton 2009)
• Deep Learning (2015, Bengio, Lecun, Hinton)
• Christopher Bishop Microsoft Research Machine Learning
• NLP Manning and Jurafsky (2012)
• Simulated Annealing
• Linear Algebra MIT Open Courseware (Gilbert Strang)
• Neural Network Introductory Video Lecture Playlist
• Deep Learning for Natural Language Processing (Stanford Lectures 2016)
• Genetic Algorithms
• Reinforcement Learning
• Deep Reinforcement Learning
• Probabilistic Graphical Models: Carnegie Mellon (2014)
• Introduction to Graphical Models
• Introduction to Probabilistic Graphical Models
• Probabilistic Graphical Models Stanford
• Convolutional Neural Networks for Visual Recognition (Stanford Lectures 2016)
• Deep Learning with Neural Networks (tensorflow)

MOOC

• Tensorflow/Deep Learning (Udacity)
• Mining Massive Data Sets Coursera (Jure Leskovec, J. McCauley. Stanford)
• Machine Learning Coursera (Andrew Ng. Stanford)
• Recommender Systems Coursera (Joseph Konstan, Michael Ekstrand. University of Minnesota)
• Reinforcement Learning (Udacity)
• Machine Learning (Udacity)

Course Pages

• Reinforcement Learning
• Convolutional Nets (Stanford Karpathy)
• Machine Learning (Oxford)

Books

• Neural Networks: Tricks of the Trade (2012)
• Neural Networks for Pattern Recognition (Bishop 1995)
• Deep Learning (Goodfellow, Bengio, Courville 2016)
• Pattern Recognition and Machine Learning. Bishop (2006)
• The Elements of Statistical Learning. Hastie, et. al. (2008)
• Pattern Classification. Duda, Hart, Stork (2012)
• Guassian Processes for Machine Learning Rasmussen, Williams (2006)
• Matrix Factorization notes