LEARN KERAS FOR DEEP NEURAL NETWORKS: A FAST-TRACK APPROACH TO MODERN DEEP LEARNING WITH PYTHON [Paperback] Moolayil

by Moolayil

Learn, understand, and implement deep neural networks in a math- and programming-friendly approach using Keras and Python. The book focuses on an end-to-end approach to developing supervised learning algorithms in regression and classification with practical business-centric use-cases implemented in Keras.



The overall book comprises three sections with two chapters in each section. The first section prepares you with all the necessary basics to get started in deep learning. Chapter 1 introduces you to the world of deep learning and its difference from machine learning, the choices of frameworks for deep learning, and the Keras ecosystem. You will cover a real-life business problem that can be solved by supervised learning algorithms with deep neural networks. You’ll tackle one use case for regression and another for classification leveraging popular Kaggle datasets.



Later, you will see an interesting and challenging part of deep hyperparameter tuning; helping you further improve your models when building robust deep learning applications. Finally, you’ll further hone your skills in deep learning and cover areas of active development and research in deep learning. 



At the end of Learn Keras for Deep Neural Networks, you will have a thorough understanding of deep learning principles and have practical hands-on experience in developing enterprise-grade deep learning solutions in Keras.



What You’ll Learn



Master fast-paced practical deep learning concepts with math- and programming-friendly abstractions. Design, develop, train, validate, and deploy deep neural networks using the Keras framework Use best practices for debugging and validating deep learning models Deploy and integrate deep learning as a service into a larger software service or product Extend deep learning principles into other popular frameworks Who This Book Is For 



Software engineers and data engineers with basic programming skills in any language and who are keen on exploring deep learning for a career move or an enterprise project.

Genres: Programming

Paperback

Published January 1, 2019

Reviews

[Farhad Azadjou · Rating 3 out of 5]

كتاب بسيار خوبي براي شروع كار با keras هست، ولي فقط پياده سازي شبكه هاي ساده ولي عميق رو با جزييات آموزش ميده و شبكه هاي CNN, RNN, LSTM و GAN رو به اختصار توضيح ميده

[Marcos Malumbres · Rating 4 out of 5]

Short introduction to Keras with basic explanations of major concepts and simple codes. The introduction of basic concepts is really good and a perfects starting point for beginners. I have a better idea of some of the basic concepts after reading this book even if I had already studied these concepts in other books before. Really crystal clear explanations in many cases. The cosing examples are quite basic but perfect for an introduction.

In addition to a few typos in some codes, I missed a bit more on critical techniques such a regularization, Dropout etc, as well as a more detailed use of CNNs, RNNs, GANs. Adding a better discussion of these chapters would make of this book a major introduction to Keras for beginners!

[Santanu · Rating 5 out of 5]

Learn Keras for Deep Learning helps you scale fast in Deep learning using the Keras Framework. The author has diligently emphasized the important aspects of deep learning with adequate theory, codes and examples to create an un-padded narrative. I go with 5 out of 5 for this book.

[Stein Karlsen · Rating 5 out of 5]

Excellent introduction to keras with interesting examples, will read again

[Pranav Srivastava · Rating 5 out of 5]

A very fast-paced, yet concise and well-written guide to learn keras for deep learning. Highly recommended for beginners. Great examples with easy to understand codes and narratives.