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Hands-On Machine Learning with Scikit-Learn and TensorFlow (全书共797页非扫描版) 评分:
Hands-On Machine Learning with Scikit-Learn and TensorFlow 完整版共797页 非扫描版 人工智能 机器学习经典书籍
上传时间:2017-09 大小:39.66MB
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Hands-On Machine Learning with Scikit-Learn and TensorFlow.zip
2020-07-29Hands-On Machine Learning with Scikit-Learn and TensorFlow.zip
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2017-03-27Hands-On Machine Learning with Scikit-Learn and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems by Aurélien Géron English | 2017 | ISBN: 1491962291 | 566 Pages | EPUB | 8.41 MB 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 frameworks—scikit-learn and TensorFlow—author Aurélien Géron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You’ll 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 you’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 Apply practical code examples without acquiring excessive machine learning theory or algorithm details
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2017-06-03Oreilly 2017最新五颗星 Deep Learning + Tensorflow + Scikit-Learn 书籍。
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