20 Best Machine Learning Books for bigginers and experts

1. The Hundred-Page Machine Learning Book

Topics covered
Anatomy of a learning algorithm
Fundamental algorithms
Neural networks and deep learning
Other forms of learning
Supervised learning and unsupervised learning

2. Programming Collective Intelligence: Building Smart Web 2.0 Applications

Topics covered
Bayesian filtering
Collaborative filtering techniques
Evolving intelligence for problem-solving
Methods for detecting groups or patterns
Non-negative matrix factorization
Search engine algorithms
Support vector machines
Ways to make predictions

3. Machine Learning for Hackers: Case Studies and Algorithms to Get you Started

Topics covered
Developing a naïve Bayesian classifier
Linear regression
Optimization techniques
Using R for querying data

4. Machine Learning

Topics covered
Genetic algorithms
Inductive logic programming
Introduction to primary approaches to machine learning
Machine learning concepts and techniques
Re-enforcement learning

5. The Elements of Statistical Learning: Data Mining, Inference, and Prediction

Topics covered
Ensemble learning
High-dimensional problems
Linear methods for classification and regression
Model inference and averaging
Neural networks
Random forests
Supervised and unsupervised learning

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