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洋書 - Hands-On Machine Learning with Scikit-Learn and TensorFlow

Hands-On Machine Learning with Scikit-Learn and TensorFlow

Hands-On Machine Learning with Scikit-Learn and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems

Hands-On Machine Learning with Scikit-Learn and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems

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