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.
Artificial intelligence
Machine Learning (Mcgraw-Hill International Edit)
An Introduction To Statistical Learning With Applications In R
Mining of Massive Datasets
Probability Theory
Probabilistic Graphical Models
All of Statistics
Python For Data Analysis
Algorithm Design
The Master Algorithm
Programming Collective Intelligence
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
Introduction to Information Retrieval
The art of R programming
More about Pattern Recognition and Machine Learning (Information Science and Statistics)