Machine Learning: An Applied Mathematics Introduction covers the essential mathematics behind all of the following topics
K Nearest Neighbours K Means Clustering Na ve Bayes Classifier Regression Methods Support Vector Machines Self-Organizing Maps Decision Trees Neural Networks Reinforcement Learning
The book includes many real-world examples from a variety of fields including
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