What to Read After Machine Learning (Mcgraw-Hill International Edit)
Readers who loved Machine Learning (Mcgraw-Hill International Edit) by Thomas Mitchell keep reaching for these 24 books. This list is built from where Machine Learning (Mcgraw-Hill International Edit) 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 Machine Learning (Mcgraw-Hill International Edit)
Pattern Recognition and Machine Learning (Information Science and Statistics)
Artificial intelligence
The Elements of Statistical Learning
Programming Collective Intelligence
Computational Complexity
Computer architecture
Modern information retrieval
Introduction to Information Retrieval
Introduction to the Theory of Computation
All of Statistics
An introduction to genetic algorithms
Elements of programming
Data mining
Data Communications and Networking (McGraw-Hill Forouzan Networking)
Computer architecture
An Introduction to Support Vector Machines and Other Kernel-based Learning Methods
Modern Operating Systems
Combinatorial Optimization
An Introduction To Statistical Learning With Applications In R
The algorithm design manual
Python For Data Analysis
Computer Networking
Joel on Software
Introduction to Algorithms
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