Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow 3e: Concepts, Tools, and Techniques to Build Intelligent Systems

Deep learning has revolutionized machine learning, making it accessible to programmers with little knowledge. This updated third edition of the best-selling book provides concrete examples, minimal theory, and production-ready Python frameworks to help you build intelligent systems. It covers techniques such as linear regression, neural networks, unsupervised learning, and neural net architectures, and uses scikit-learn, Keras, and TensorFlow to implement them.

Format: Paperback / softback
Length: 850 pages
Publication date: 18 October 2022
Publisher: O'Reilly Media

Deep learning has revolutionized the field of machine learning, making it accessible to programmers with minimal knowledge. This best-selling book provides concrete examples, minimal theory, and production-ready Python frameworks (scikit-learn, Keras, and TensorFlow) to help readers gain an intuitive understanding of building intelligent systems. Author Aurelien Geron covers a range of techniques, from simple linear regression to deep neural networks, with numerous code examples and exercises. With programming experience as the only prerequisite, readers can use scikit-learn to track a machine learning project end-to-end, explore various models, including support vector machines, decision trees, random forests, and ensemble methods, exploit unsupervised learning techniques such as dimensionality reduction, clustering, and anomaly detection, dive into neural net architectures, including convolutional nets, recurrent nets, generative adversarial networks, and transformers, use TensorFlow and Keras to build and train neural nets for computer vision, natural language processing, generative models, and deep reinforcement learning, and train neural nets using multiple GPUs and deploy them at scale using Google's Vertex AI.

ISBN-13: 9781098125974
Edition number: 3 Revised edition