Loading...
Introduction to Machine Learning
Introduction to Machine Learning is a comprehensive textbook on the subject, covering a broad array of topics not usually included in introductory machine learning texts. Subjects include supervised learning; Bayesian decision theory; parametric, semiparametric, and nonparametric methods; multivaria...
| Main Author: | |
|---|---|
| Format: | Printed Book |
| Published: |
Patparganj, Delhi
PHI LearningPrivate limited
2018
|
| Edition: | 3rd ed [ eastern Economy Edition ] |
| Subjects: |
Table of Contents:
- Preface Notations 1. Introduction 2 Supervised Learning 3. Bayesian Decision Theory 4. Parametric Methods 5. Multivariate Methods 6. Dimensionality Reduction 7. Clustering 8. Nonparametric Methods 9. Decision Trees 10. Linear Discrimination 11. Multilayer Perceptrons 12. Local Models 13. Kernel Machines 14. Graphical Models 15. Hidden Markov Models 16. Bayesian Estimation 17. Combining Multiple Learners 18. Reinforcement Learning 19. Design and Analysis of Machine Learning Experiments Printed Pages: 635.