What to Read After Pattern Recognition and Machine Learning (Information Science and Statistics)
Readers who loved Pattern Recognition and Machine Learning (Information Science and Statistics) by Christopher M. Bishop keep reaching for these 24 books. This list is built from where Pattern Recognition and Machine Learning (Information Science and Statistics) is read alongside other books across reader co-reads and book lists. The more independent sources agree on a title, the higher it ranks.
Books to read after Pattern Recognition and Machine Learning (Information Science and Statistics)
The Elements of Statistical Learning
INFORMATION THEORY, INFERENCE, AND LEARNING ALGORITHMS.
Machine Learning
Pattern Classification
Artificial Intelligence
Machine Learning (Mcgraw-Hill International Edit)
Probability Theory
An Introduction To Statistical Learning With Applications In R
Mining of Massive Datasets
All of Statistics
Probabilistic Graphical Models
Python For Data Analysis
Algorithm Design
Programming Collective Intelligence
The Master Algorithm
An Introduction to Statistical Learning
Doing Bayesian Data Analysis
Quantitative Trading
Causality
Paradigms of Artificial Intelligence
Probabilistic Reasoning in Intelligent Systems
An Introduction to Support Vector Machines and Other Kernel-based Learning Methods
Data Mining
R Cookbook
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