Hands-On Machine Learning with Scikit-Learn and TensorFlow
- 作者: Aurélien Géron
- 出版社/メーカー: O'Reilly Media
- 発売日: 2017/04/09
- メディア: ペーパーバック
- この商品を含むブログ (1件) を見る
Table of Contents
I. The Fundamentals of Machine Learning
- 1. The Machine Learning Landscape
- 2. End-to-End Machine Learning Project
- 3. Classification
- 4. Training Models
- 5. Support Vector Machines
- 6. Decision Trees
- 7. Ensemble Learning and Random Forests
- 8. Dimensionality Reduction
II. Neural Networks and Deep Learning
- 9. Up and Running with TensorFlow
- 10. Introduction to Artificial Neural Networks
- 11. Training Deep Neural Nets
- 12. Distributing TensorFlow Across Devices and Servers
- 13. Convolutional Neural Networks
- 14. Recurrent Neural Networks
- 15. Autoencoders
- 16. Reinforcement Learning
Appendix
- A. Exercise Solutions
- B. Machine Learning Project Checklist
- C. SVM Dual Problem
- D. Autodiff
- E. Other Popular ANN Architectures