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Publisher's Summary

This book will introduce you to various deep learning models in Keras, and you will see how different neural networks can be used in real-world examples, as well as in various scientific fields. You will explore various Keras algorithms like the simplest linear regression or more complex deep convolutional networks. You will get to know what the difference between supervised and unsupervised deep learning is, and you will be able to implement various algorithms in Keras by yourself as you follow this step-by-step guide in this book.

You will explore various applications of deep learning models such as speech recognition systems, natural language processing and video game development. A whole new world will open in front of you. By the time you reach the final minute of this book, you will be a Keras expert and ready for your deep-learning projects.

There is so much to learn in this book about deep learning with Keras, and I do invite you to grab your copy today and get started!

By listening to this book you will discover:

  • Deep neural network
  • Neural network elements
  • Keras models
  • Sequential model
  • Functional API model
  • Keras layers
  • Core Keras layers
  • Convolutional Keras layers
  • Recurrent Keras layers
  • Deep learning algorithms
  • Supervised learning algorithms
  • Applications of deep learning models
  • Automatic speech and image recognition
  • Natural language processing
  • Video game development
  • Real world applications
  • And of course, much more!

Get this book today, and learn more about deep learning with Keras!

©2017 Anthony Williams (P)2017 Anthony Williams

What members say

Average Customer Ratings

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Nice book...

A nice feature of this book is that it solves a problem using several methods that increase in complexity; this is done in order to highlight the power of deeper and more sophisticated neural nets. Also, the book describes extensively the different features of Keras which is hard to find elsewhere. Overall, I highly recommend this book to technically-proficient deep learning enthusiasts.

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Develop Deep Learning Engineering Skill

This book has a number of well worked examples, and I have found only a minor flaw in the code which can be fixed with a quick Google search, so it is nothing to worry about. Then again, I do not know of any book with code examples that has code that works right away (i.e. where every single line of code from the book works right away). The Keras web site is nice, but for somebody like me (I'm a data scientist, not a "real programmer" or developer) code examples are really needed to understand how to apply the concepts. So I strongly suggest this book. Thank you Anthony Williams for writing it!

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Deep Learning courses

As a developer that has done a number of online Machine Learning/Deep Learning courses and a bit of reading/experimenting in the area, I enjoyed the book. The initial chapters provided a nice refresher/bridge into Deep Learning along with easy to follow instructions on getting up and going on Keras. The remainder of the book provide practical code examples of using Keras in a number of areas that were of specific interest to me and very helpful. I would recommend this book.

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Great Introduction to Using Keras

That having been said, this book is a great introduction to coding up deep learning algorithms in Keras. There are sufficient citations and followups for each chapter and the authors also show the detailed code and expected outputs. The reader should already have some experience with python and a basic understanding of neural networks.

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Worth reading!

This is a very practical guide and implement various deep-learning algorithms in Keras and its very well explained that are easy to understand. It also provide a step by step functions on a large neural network and everything you need to know. Worth reading!

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A very nice resource

Deep Learning with Keras is a great resource to get hands on Deep Learning experience using the Keras library in Python. The book tackles many interesting subjects some of which are hard to find elsewhere including Generative Adversarial Nets and Reinforcement Learning. A nice feature of this book is that it solves a problem using several methods that increase in complexity; this is done in order to highlight the power of deeper and more sophisticated neural nets. Also, the book describes extensively the different features of Keras which is hard to find elsewhere.

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Practical, hands on and with a generous set of sam

Practical, hands on and with a generous set of samples covering even some rather recent topics. Gets the job done. There are sufficient citations and followups for each chapter and the authors also show the detailed code and expected outputs. The listeners should already have some experience with python and a basic understanding of neural networks.

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Highly Recommended

This is a very practical guide and implement various deep-learning algorithms in Keras and its very well explained that are easy to understand.

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It is a great book. It is not a textbook on deep l

The difference between supervised and unsupervised deep learning and you will be able to implement various algorithms in Keras by yourself as you follow step-by-step guide in this book.

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Good information

This book will introduce me to various deep learning models in Keras, and l see how different neural networks can be used in real-world examples as well as in various scientific fields!!