(full color) hands-on machine learning with scikit-learn, keras, and tensorflow: 2nd edition

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Описание

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 Tensor Flow--author Aurelien Geron 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. \nn \n

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- - Explore the machine learning landscape, particularly neural nets
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- Use Scikit-Learn to track an example machine-learning project end-to-end
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- Explore several training models, including support vector machines, decision trees, random forests, and ensemble methods
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- - Use the Tensor Flow library to build and train neural nets
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- - Dive into neural net architectures, including convolutional nets, recurrent nets, and deep reinforcement learning
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- - Learn techniques for training and scaling deep neural nets.
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Також купити книгу Hands-On Machine Learning with Scikit-Learn, Keras, and
TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems 2nd
Edition, Aurelien Geron можливо по посиланню:

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