- The Elements of Statistical Learning, Hastie, et al. [pdf]
- Deep Learning Book, MIT
- Artificial Intelligence: A Modern Approach, Stuart Russell and Peter Norvig.
- Information Theory, Inference, and Learning Algorithms, David J. C. MacKay, 2003.
- Pattern Recognition and Machine Learning, Christopher Bishop, 2006.
- Machine Learning: A Probabilistic Perspective, Kevin P. Murphy, 2012.
- Machine Learning, Andrew Ng [[Coursera]] (https://www.coursera.org/learn/machine-learning#)
- Neural Networks for Machine Learning, University of Toronto, Geoffrey Hinton[[Coursera]] (https://www.coursera.org/learn/neural-networks/home/info)
- INFO8010 - Deep Learning, Gilles Louppe.
- Scikit-learn: http://scikit-learn.org/stable/index.html
- Tensorflow: https://www.tensorflow.org/
- Variational Bayes and Beyond: Bayesian Inference for Big Data, Tamara Broderick. https://www.youtube.com/watch?v=DYRK0-_K2UU
- Variational Inference: A Review for Statisticians, David M. Blei, Alp Kucukelbir, Jon D. McAuliffe. https://arxiv.org/abs/1601.00670