Packt+ | Advance your knowledge in tech

0

All Products

Best Sellers

New Releases

Books

Videos

Audiobooks

Free Learning

Deep Learning with Keras

You're reading from Deep Learning with Keras Implementing deep learning models and neural networks with the power of Python

Product type Paperback

Published in Apr 2017

Publisher Packt

ISBN-13 9781787128422

Length 318 pages

Edition 1st Edition

Languages

Python

Tools

Keras

Concepts

Deep Learning

Authors (2):

Antonio Gulli

Sujit Pal

View More author details

Table of Contents (16) Chapters

Title Page

Credits

About the Authors

About the Reviewer

www.PacktPub.com

Customer Feedback

Preface

1. Neural Networks Foundations FREE CHAPTER

2. Keras Installation and API

3. Deep Learning with ConvNets

4. Generative Adversarial Networks and WaveNet

5. Word Embeddings

6. Recurrent Neural Network — RNN

7. Additional Deep Learning Models

8. AI Game Playing

9. Conclusion

Keras 2.0 — what is new

Summary

In this chapter, we discussed GANs. A GAN typically consists of two networks; one is trained to forge synthetic data that looks authentic, and the second is trained to discriminate authentic data against forged data. The two networks continuously compete, and in doing so, they keep improving each other. We reviewed an open source code, learning to forge MNIST and CIFAR-10 images that look authentic. In addition, we discussed WaveNet, a deep generative network proposed by Google DeepMind for teaching computers how to reproduce human voices and musical instruments with impressive quality. WaveNet directly generates raw audio with a parametric text-to-speech approach based on dilated convolutional networks. Dilated convolutional networks are a special kind of ConvNets where convolution filters have holes, allowing the receptive field to grow exponentially in depth and therefore efficiently cover thousands of audio time-steps. DeepMind showed how it is possible to use WaveNet to synthesize...

The rest of the chapter is locked

Register for a free Packt account to unlock a world of extra content!

A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.

Unlock this book and the full library FREE for 7 days

Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of

Start free trial

Renews at $15.99/month. Cancel anytime

Authors (2)

Antonio Gulli

Antonio Gulli

Antonio Gulli has a passion for establishing and managing global technological talent for innovation and execution. His core expertise is in cloud computing, deep learning, and search engines. Currently, Antonio works for Google in the Cloud Office of the CTO in Zurich, working on Search, Cloud Infra, Sovereignty, and Conversational AI.

See other products by Antonio Gulli

Sujit Pal

Sujit Pal

Sujit Pal is a Technology Research Director at Elsevier Labs, an advanced technology group within the Reed-Elsevier Group of companies. His interests include semantic search, natural language processing, machine learning, and deep learning. At Elsevier, he has worked on several initiatives involving search quality measurement and improvement, image classification and duplicate detection, and annotation and ontology development for medical and scientific corpora.

See other products by Sujit Pal

Other recommended products

Related to this chapter

Deep Learning with TensorFlow 2 and Keras

Deep Learning with TensorFlow 2 and Keras

Deep Learning with TensorFlow 2 and Keras, Second Edition teaches deep learning techniques alongside TensorFlow (TF) and Keras. The book introduces neural networks with TensorFlow, runs through the main applications, covers two working example apps, and then dives into TF and cloudin production, TF mobile, and using TensorFlow with AutoML.

Dec 2019 21h 32m

TensorFlow 1.x Deep Learning Cookbook

TensorFlow 1.x Deep Learning Cookbook

Deep Neural Networks (DNNs) have achieved a lot of success in the field of computer vision, speech recognition, and natural language processing. In this book, you will learn how to efficiently use TensorFlow, Google's open source framework for deep learning, and implement different deep learning networks with easy to follow independent recipes.

Dec 2017 17h 52m

Python Deep Learning Cookbook

Python Deep Learning Cookbook

Deep Learning is a rapidly evolving field of Machine Learning science which gives machines the ability to learn from information. This book contains detailed recipes to tackle with the common and not so common problems while dealing with deep learning algorithms and models in Python. You will benefit from this book by finding technical solutions to the issues presented, along with a detailed explanation of the solutions, and a discussion on corresponding pros and cons of implementing the proposed solution using Theano, Tensorflow, MXNet, and Keras. You'll come across recipes on data pre-processing, network models and topologies, supervised and unsupervised learning presented in a “solution to problem” fashion.

Oct 2017 11h 0m

Neural Networks with Keras Cookbook

Neural Networks with Keras Cookbook

This book presents solutions to the majority of the challenges you will face while training neural networks to solve deep learning problems. It covers the trending deep learning architectures used in industry and tackles a variety of use cases in computer vision, text processing, audio analysis, recommender systems, and game bots

Feb 2019 18h 56m

Keras Deep Learning Cookbook

Keras Deep Learning Cookbook

This book gives you a practical, hands-on understanding of how you can leverage the power of Python and Keras to perform effective deep learning. It presents a unique problem-solution approach to tackle various problems in training different types of neural networks while taking care of the speed and accuracy of these models

Oct 2018 8h 24m

Generative Adversarial Networks Cookbook

Generative Adversarial Networks Cookbook

Generative Adversarial Networks have opened up many new possibilities in the machine learning domain. This book is all you need to implement different types of GANs using TensorFlow and Keras, in order to provide optimized and efficient deep learning solutions.

Dec 2018 8h 56m

Hands-On Generative Adversarial Networks with Keras

Hands-On Generative Adversarial Networks with Keras

This book will explore deep learning and generative models, and their applications in artificial intelligence. You will learn to evaluate and improve your GAN models by eliminating challenges that are encountered in real-world applications. You will implement GAN architectures in various domains such as computer vision, NLP, and audio processing

Generative Adversarial Networks Projects

Generative Adversarial Networks Projects

In this book, we will use different complexities of datasets in order to build end-to-end projects. With every chapter, the level of complexity and operations will become advanced. It consists of 8 full-fledged projects covering approaches such as 3D-GAN, Age-cGAN, DCGAN, SRGAN, StackGAN, and CycleGAN with real-world use cases.

Jan 2019 10h 32m

Mastering TensorFlow 1.x

Mastering TensorFlow 1.x

We cover advanced deep learning concepts (such as transfer learning, generative adversarial models, and reinforcement learning), and implement them using TensorFlow and Keras. We cover how to build and deploy at scale with distributed models. You will learn to build TensorFlow models using R, Keras, TensorFlow Learn, TensorFlow Slim and Sonnet

Jan 2018 15h 48m

Hands-On Convolutional Neural Networks with TensorFlow

Hands-On Convolutional Neural Networks with TensorFlow

Convolutional Neural Networks (CNN) are one of the most popular architectures used in computer vision apps. This book is an introduction to CNNs through solving real-world problems in deep learning while teaching you their implementation in popular Python library - TensorFlow. By the end of the book, you will be training CNNs in no time!

Advanced Deep Learning with Keras

Advanced Deep Learning with Keras

This book covers advanced deep learning techniques to create successful AI. Using MLPs, CNNs, and RNNs as building blocks to more advanced techniques, you'll study deep neural network architectures, Autoencoders, Generative Adversarial Networks (GANs), Variational AutoEncoders (VAEs), and Deep Reinforcement Learning (DRL) critical to many cutting-edge AI results.

Oct 2018 12h 16m

Deep Learning for Natural Language Processing

Deep Learning for Natural Language Processing

Starting with the basics, this book teaches you how to choose from the various text pre-processing techniques and select the best model from the several neural network architectures for NLP issues.

Jun 2019 12h 24m

Personalised recommendations for you

Based on your interests and search pattern

Mathematics of Machine Learning

Mathematics of Machine Learning

Deepen your theoretical knowledge and enhance your ability to solve complex machine learning problems with structured guidance. Gain the confidence to engage with advanced ML literature and tailor algorithms to meet your project requirements.

May 2025 24h 20m

Generative AI with Python and PyTorch

Generative AI with Python and PyTorch

Learn how to create images and text using VAEs, GANs, LSTMs, and transformers. Implement applications in natural language processing and computer vision through practical tutorials.

Mar 2025 15h 0m

Practical Generative AI with ChatGPT

Practical Generative AI with ChatGPT

This book helps you unlock ChatGPT's potential to make your working life better. From prompt engineering to creating custom GPTs, you'll enhance your productivity, creativity, and efficiency with practical insights and advanced techniques.

Apr 2025 12h 52m

Generative AI with LangChain

Generative AI with LangChain

Gain a solid foundation in LangChain, agentic AI, and LangGraph, and learn to build production-ready systems with multi-agent architectures, advanced RAG pipelines, Tree of Thought reasoning, agent handoffs, and fine-grained error handling.

May 2025 15h 52m

Architecting Power BI Solutions in Microsoft Fabric

Architecting Power BI Solutions in Microsoft Fabric

Power BI provides several options to solve common data problems, and designing the correct solution for each scenario can be a daunting task. This book makes it easier by guiding you through designing optimal solutions using Power BI.

Apr 2025 14h 16m

Microsoft Identity and Access Administrator SC-300 Exam Guide

Microsoft Identity and Access Administrator SC-300 Exam Guide

This comprehensive guide covers key topics such as Microsoft Entra ID implementation, authentication and access management, external user management, and hybrid identity solutions, providing practical insights and techniques for SC-300 exam success.

Mar 2025 19h 48m

LLM Design Patterns

LLM Design Patterns

This book helps you gain practical skills to develop and deploy LLMs. You'll learn data prep, training, pruning, quantization, and evaluation, as well as explore RAG, advanced prompting, and optimization to build robust, scalable language models.

May 2025 17h 48m

Tableau Cookbook for Experienced Professionals

Tableau Cookbook for Experienced Professionals

Advance your Tableau knowledge beyond the basics, streamline dashboard performance, tackle advanced geospatial challenges, and unlock API potential while fortifying your corporate data infrastructure with proven best practices.

Apr 2025 12h 24m

Time Series Analysis with Spark

Time Series Analysis with Spark

This book offers a complete guide to time series analysis with Apache Spark and Databricks, covering essential concepts and advanced techniques including Generative AI to equip readers with skills for real-world challenges across industries.

Mar 2025 9h 56m

Hands-On Artificial Intelligence for IoT

Hands-On Artificial Intelligence for IoT

Transform IoT systems with the power of artificial intelligence using this hands-on guide. Dive into practical techniques and expert insights to innovate and optimize your IoT devices, making them smarter and more efficient.

May 2025 15h 44m