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Part I. Foundation
Chapter 1. Introduction
Chapter 2. Numerical Vectors
Chapter 3. Data Encoding
Chapter 4. Simple Machine Learning Algorithms
Part II. Supervised Learning
Chapter 5. Instance based Learning
Chapter 6. Probabilistic Learning
Chapter 7. Decision Tree
Chapter 8. Support Vector Machine
Part III. Unsupervised Learning
Chapter 9. Simple Clustering Algorithms
Chapter 10. K Means Algorithm
Chapter 11. EM Algorithm
Chapter 12. Advanced Clustering
Part IV. Advanced Topics
Chapter 13. Ensemble Learning
Chapter 14. Semi-Supervised Learning
Chapter 15. Temporal Learning
Chapter 16. Reinforcement Learning.

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