Machine Learning: The Art and Science of Algorithms that Make Sense of Data > 인공지능

Table of Contents

Prologue: a machine learning sampler
1. The ingredients of machine learning
2. Binary classification and related tasks
3. Beyond binary classification
4. Concept learning
5. Tree models
6. Rule models
7. Linear models
8. Distance-based models
9. Probabilistic models
10. Features
11. In brief: model ensembles
12. In brief: machine learning experiments
Epilogue: where to go from here
Important points to remember
Bibliography
Index.