12 books in series

Adaptive Computation and Machine Learning

Adaptive Computation and Machine Learning is a 11-book series with 12 primary works first released in 1993 with contributions by Peter Spirtes, Clark Glymour, Richard Scheines, Pierre Baldi, Søren Brunak, Ethem Alpaydin, Carl Edward Rasmussen, Christopher K. I. Williams, Daphne Koller, Nir Friedman, Robert E. Schapire, Yoav Freund, Mehryar Mohri, Afshin Rostamizadeh, Ameet Talwalkar, Ian Goodfellow, Yoshua Bengio, Aaron Courville, Kevin P. Murphy, Marc G. Bellemare, Will Dabney, and Mark Rowland.

Details	Rating	Readers Count
Deep Learning Ian Goodfellow Yoshua Bengio Aaron Courville	4.8	7 reads
Causation, Prediction, and Search Causation, Prediction, and Search Peter Spirtes Clark Glymour Richard Scheines	0	0 reads
Machine Learning: A Probabilistic Perspective Kevin P. Murphy	0	2 reads
Introduction to Machine Learning Introduction to Machine Learning Ethem Alpaydin	0	1 read
Gaussian Processes for Machine Learning Carl Edward Rasmussen Christopher K. I. Williams	0	0 reads
Probabilistic Machine Learning: An Introduction Kevin P. Murphy	0	0 reads
Boosting: Foundations and Algorithms Robert E. Schapire Yoav Freund	0	0 reads
Distributional Reinforcement Learning Marc G. Bellemare Will Dabney Mark Rowland	0	0 reads
Bioinformatics: The Machine Learning Approach Pierre Baldi Søren Brunak	0	0 reads
Introduction to Statistical Relational Learning	0	0 reads
Foundations of Machine Learning Mehryar Mohri Afshin Rostamizadeh Ameet Talwalkar	0	0 reads
Probabilistic Graphical Models: Principles and Techniques Daphne Koller Nir Friedman	0	0 reads