深度学习神经网络，用R语言描述

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Deep Learning Made Easy with R_ (2016).pdf (5.52 MB, 需要: 1 个论坛币)

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深度学习-R语言描述
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深度学习神经网络，用R语言描述的著作。

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关键词：神经网络 深度学习 R语言 神经网 网络

thank you very much
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我来补一下本书的介绍吧，希望对大家有所帮助

作者：N.D Lewis
介绍：
Master Deep Learning with this fun, practical, hands on guide.
With the explosion of big data deep learning is now on the radar. Large companies such as Google, Microsoft, and Facebook have taken notice, and are actively growing in-house deep learning teams. Other large corporations are quickly building out their own teams. If you want to join the ranks of today's top data scientists take advantage of this valuable book. It will help you get started. It reveals how deep learning models work, and takes you under the hood with an easy to follow process showing you how to build them faster than you imagined possible using the powerful, free R predictive analytics package.

Bestselling decision scientist Dr. N.D Lewis shows you the shortcut up the steep steps to the very top. It's easier than you think. Through a simple to follow process you will learn how to build the most successful deep learning models used for learning from data. Once you have mastered the process, it will be easy for you to translate your knowledge into your own powerful applications.

If you want to accelerate your progress, discover the best in deep learning and act on what you have learned, this book is the place to get started.

YOU'LL LEARN HOW TO:
· Understand Deep Neural Networks
· Use Autoencoders
· Unleash the power of Stacked Autoencoders
· Leverage the Restricted Boltzmann Machine
· Develop Recurrent Neural Networks
· Master Deep Belief Networks
Everything you need to get started is contained within this book. It is your detailed, practical, tactical hands on guide - the ultimate cheat sheet for deep learning mastery. A book for everyone interested in machine learning, predictive analytic techniques, neural networks and decision science. Start building smarter models today using R!

是新的资料，多谢！

很好的资料，感谢楼主分享！

谢谢分享

thanks

thank you very much