Hands-On Machine Learning with Scikit-Learn, Keras & TensorFlow 2
Concepts, Tools, and Techniques to Build Intelligent Systems
This is my implementation of the examples in Aurelien Geron's book Hands-On Machine Learning with Scikit-Learn, Keras & TensorFlow (2nd Edition)
Part I. The Fundamentals of Machine Learning
Chapter 1: The Machine Learning Landscape
Chapter 2: End-to-End Machine Learning Project
Chapter 3: Classification
Chapter 4: Trainning Models
Chapter 5: Support Vector Machines
Chapter 6: Decision Trees
Chapter 7: Ensamble Learning and Random Forests
Chapter 8: Dimensionality Reduction
Chapter 9: Unsupervised Learning Techniques
Part II. Neural Networks and Deep Learning
Chapter 10: Introduction to Artificial Neural Networks with Keras
Chapter 11: Trainning Deep Neural Networks
Chapter 12: Custom Models and Trainning with TensorFlow
Chapter 13: Loading and Preprocessing Data with TensorFlow
Chapter 14: Deep Computer Vision Using COnvolutional Neural Networks
Chapter 15: Preprocessing Sequences Using RNNs and CNNs
Chapter 16: Natural Language Processing with RNNs and Attention
Chapter 17: Representation Learning and Generative Learning Using Autoencoders and GANs
Chapter 18: Reinforcement Learning
Chapter 19: Trainning and Deploying TensorFlow Models at Scale
If you want to contribute or fix some bugs, feel free to open an issue or make a pull request.