- Bayesian Reasoning and Machine Learning
- Computer Vision: Algorithms and Applications
- David MacKay: Information Theory, Pattern Recognition and Neural Networks
- Deep Learning
- Elements of Statistical Learning: data mining, inference, and prediction
- Introduction to Data Mining
- Introduction to Information Retrieval
- Reinforcement learning: : An Introduction
- Think Stats : Probability and Statistics for Programmers
A-Zあ-ん順です。 最近強化学習の本でよく行ったり来たりするので一旦メモ。読んだことあるものもないものもごっちゃになってます。2000年より古いものは消しました。
Bayesian Reasoning and Machine Learning
by Barber, D, published by Cambridge University Press
David Barber : Brml - Home Page browse
Computer Vision: Algorithms and Applications
by Richard Szeliski
Computer Vision: Algorithms and Applications
David MacKay: Information Theory, Pattern Recognition and Neural Networks
by David MacKay, published by Cambridge University Press
David MacKay: Information Theory, Pattern Recognition and Neural Networks: The Book
Deep Learning
by Ian Goodfellow and Yoshua Bengio and Aaron Courville, published by MIT Press
Elements of Statistical Learning: data mining, inference, and prediction
by Trevor Hastie, Robert Tibshirani, Jerome Friedman,
Elements of Statistical Learning: data mining, inference, and prediction. 2nd Edition.
Introduction to Data Mining
by Pang-Ning Tan, Michael Steinbach, Vipin Kumar
Introduction to Information Retrieval
by Christopher D. Manning, Prabhakar Raghavan and Hinrich Schütze, published by Cambridge University Press
Introduction to Information Retrieval
Reinforcement learning: : An Introduction
by Richard S. Sutton and Andrew G. Barto, published by MIT press
Sutton & Barto Book: Reinforcement Learning: An Introduction
Think Stats : Probability and Statistics for Programmers
by Allen B. Downey, published by O'Reilly Media.
