Through a series of recent 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 practical book shows you how. By using concrete examples, minimal theory, and two production-ready Python framework helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You are learn a range of techniques, starting with simple linear regression and progressing to deep neural networks. With exercises in each chapter to help you apply what youâ??ve learned, all you need is programming experience to get started. Explore the machine learning landscape, particularly neural nets. Use Scikit-Learn to track an example machine-learning project end-to-end. Explore several training models, including support vector machines, decision trees, random forests, and ensemble methods. Use the TensorFlow library to build and train neural nets. Dive into neural net architectures, including convolutional nets, recurrent nets, and deep reinforcement learning. Learn techniques for training and scaling deep neural nets.

Mã ngôn ngữ:	eng
Chỉ số phân loại:	006.3
Tác giả:	Géron, Aurélien
Thông tin nhan đề:	Hands On Machine Learning with Scikit Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems
Xuẩt bản,phát hành:	Canada. O'Reilly Media. 2019
Mô tả vật lý:	819p.
Từ khóa:	Concepts. Scikit Learn. Techniques to Build Intelligent Systems. Tools

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