concepts, tools, and techniques to build intelligent systems Géron, Aurélien creator author. text bibliography cc Beijing O'Reilly Media 2025 Third edition. monographic eng xxv, 834 pages : illustrations (chiefly color). "Through a recent series of breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This best-selling book uses concrete examples, minimal theory, and production-ready Python frameworks--scikit-learn, Keras, and TensorFlow--to help you gain an intuitive understanding of the concepts and tools for building intelligent systems. With this updated third edition, author Aurelien Geron explores a range of techniques, starting with simple linear regression and progressing to deep neural networks. Numerous code examples and exercises throughout the book help you apply what you've learned. Programming experience is all you need to get started" The machine learning landscape -- End-to-end machine learning project -- Classification -- Training models -- Support vector machines -- Decision trees -- Ensemble learning and random forests -- Dimensionality reduction -- Unsupervised learning techniques -- Introduction to artificial neural networks with Keras -- Training deep neural networks -- Custom models and training with TensorFlow -- Loading and preprocessing data with TensorFlow -- Deep computer vision using convolutional neural networks -- Processing sequences using RNNs and CNNs -- Natural language processing with RNNs and attention -- Autoencoders, GANs, and diffusion models -- Reinforcement learning -- Training and deploying TensorFlow models at scale. specialized Aurélien Géron. Includes bibliographical references and index. Texto en inglés. Python (Lenguaje de programación) Python (Computer program language) Machine learning Artificial intelligence 006.31 9781098125974 UKMGB 260616 20260616102615.0 991014935821404990 eng