All books are available in Library of Genesis
Data engineering principles
Basics of probabilistic modelling
- E. T. Jaynes. Probability Theory: The Logic of Science (2003, Cambridge University Press)
- Sabine Hossenfelder. The Reproducibility Crisis
Problems with non-informative priors
Sequence models and belief propagation
- Judea Pearl. Probabilistic Reasoning in Intelligent Systems Networks of Plausible Inference (1988, Morgan Kaufmann)
- Finn V. Jensen; Thomas D. Nielsen. Bayesian Networks and Decision Graphs (2007, Spinger)
- Daniel Jurafsky & James H. Martin: Speech and Language Processing
Normal distributions
- Andrew Blake and Pushmeet Kohli. Markov Random Fields for Vision and Image Processing (2011, The MIT Press)
- John Lafferty and Andrew McCallum. Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data (2001)
- Cookbook for EM-algorithms