Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow

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Content

Part I. The Fundamentals of Machine Learning

1. Machine Learning Landscape
2. End-to End Machine Learning Project
3. Classification
4. Training Models
5. Support Vector Machines
6. Decision Trees
7. Esemble Learning and Random Forests
8. Dimensionality Reduction
9. Unsupervised Learning Techniques

Part II. Neural Networks and Deep Learning

10. Introduction to Artificial Neural Networks with Keras
11. Training Deep Neural Networks