- A Brief Introduction to Machine Learning for Engineers – Osvaldo Simeone (PDF)
- A Brief Introduction to Neural Networks
- A Course in Machine Learning (PDF)
- A First Encounter with Machine Learning (PDF)
- An Introduction to Statistical Learning – Gareth James, Daniela Witten, Trevor Hastie and Robert Tibshirani
- Bayesian Reasoning and Machine Learning
- Deep Learning – Ian Goodfellow, Yoshua Bengio and Aaron Courville
- Foundations of Machine Learning, Second Edition – Mehryar Mohri, Afshin Rostamizadeh, Ameet Talwalkar
- Gaussian Processes for Machine Learning
- Information Theory, Inference, and Learning Algorithms
- Interpretable Machine Learning – Christoph Molnar
- Introduction to CNTK Succinctly – James McCaffrey
- Introduction to Machine Learning – Amnon Shashua
- Keras Succinctly – James McCaffrey
- Learn Tensorflow – Jupyter Notebooks
- Learning Deep Architectures for AI (PDF)
- Machine Learning
- Machine Learning for Data Streams – Albert Bifet, Ricard Gavaldà, Geoff Holmes, Bernhard Pfahringer
- Machine Learning, Neural and Statistical Classification
- Neural Networks and Deep Learning
- Probabilistic Models in the Study of Language (Draft, with R code)
- Reinforcement Learning: An Introduction (Draft) – Richard S. Sutton, Andrew G. Barto (PDF)
- Speech and Language Processing (3rd Edition Draft) – Daniel Jurafsky, James H. Martin (PDF)
- The Elements of Statistical Learning – Trevor Hastie, Robert Tibshirani, and Jerome Friedman
- The LION Way: Machine Learning plus Intelligent Optimization – Roberto Battiti, Mauro Brunato (PDF)
- The Python Game Book
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