What to Read After INFORMATION THEORY, INFERENCE, AND LEARNING ALGORITHMS.
Readers who loved INFORMATION THEORY, INFERENCE, AND LEARNING ALGORITHMS. by David J.C. MacKay keep reaching for these 24 books. This list is built from where INFORMATION THEORY, INFERENCE, AND LEARNING ALGORITHMS. 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 INFORMATION THEORY, INFERENCE, AND LEARNING ALGORITHMS.
Pattern Recognition and Machine Learning (Information Science and Statistics)
Elements of Information Theory
The Elements of Statistical Learning
Probability Theory
Concrete mathematics
Introduction to Information Retrieval
The emotion machine
All of Statistics
Quantum computation and quantum information
The Princeton Companion to Mathematics
Feynman lectures on computation
An introduction to information theory
The computer and the brain
Mining of Massive Datasets
Mathematical Theory of Communication
An introduction to genetic algorithms
Algebra
Theoretical Neuroscience
Causality
Schaum's outline of discrete mathematics
The mathematical theory of communication
Probabilistic Graphical Models
Measurement
Computational Complexity
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