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

This text is an excerpt from Aurélien Géron's "Hands-On Machine Learning with Scikit-Learn, Keras & TensorFlow," second edition. The book comprehensively covers machine learning concepts and techniques, progressing from basic algorithms like linear regression to advanced deep learning methods. It emphasizes practical application using Python libraries, including Scikit-learn, Keras, and TensorFlow. The excerpt showcases various topics, such as data preparation, model selection, hyperparameter tuning, and evaluating model performance. Specific algorithms and techniques discussed include support vector machines, ensemble methods (like random forests and boosting), dimensionality reduction, and unsupervised learning approaches (like K-Means clustering and Gaussian mixture models). Finally, the excerpt also details building custom models and using TensorFlow's lower-level API.