Deep.Learning.Made.Easy.with.R.A.Gentle.Introduction.For.Data.Science

时间:2019-02-03 12:10:40
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文件名称:Deep.Learning.Made.Easy.with.R.A.Gentle.Introduction.For.Data.Science

文件大小:5.88MB

文件格式:PDF

更新时间:2019-02-03 12:10:40

R Deep Learning

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! Buy the book today. Your next big breakthrough using deep learning is only a page away! Table of Contents Chapter 1 Introduction Chapter 2 Deep Neural Networks Chapter 3 Elman Neural Networks Chapter 4 Jordan Neural Networks Chapter 5 The Secret to the Autoencoder Chapter 6 The Stacked Autoencoder in a Nutshell Chapter 7 Restricted Boltzmann Machines Chapter 8 Deep Belief Networks


网友评论

  • 说不错,对R在机器学习上的应用解释的很清晰!
  • 非常不错!!!
  • 不错 很好 不错 很好
  • 书是2016年版的,全书主要介绍了一些深度学习算法的r包及其应用。
  • 谢谢分享!