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Keras Deep Learning Cookbook
Keras Deep Learning Cookbook

Keras Deep Learning Cookbook: Over 30 recipes for implementing deep neural networks in Python

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Profile Icon Dua Profile Icon Sujit Pal Profile Icon Ghotra
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€18.99 per month
Full star icon Empty star icon Empty star icon Empty star icon Empty star icon 1 (1 Ratings)
Paperback Oct 2018 252 pages 1st Edition
eBook
€20.99 €23.99
Paperback
€29.99
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Renews at €18.99p/m
Arrow left icon
Profile Icon Dua Profile Icon Sujit Pal Profile Icon Ghotra
Arrow right icon
€18.99 per month
Full star icon Empty star icon Empty star icon Empty star icon Empty star icon 1 (1 Ratings)
Paperback Oct 2018 252 pages 1st Edition
eBook
€20.99 €23.99
Paperback
€29.99
Subscription
Free Trial
Renews at €18.99p/m
eBook
€20.99 €23.99
Paperback
€29.99
Subscription
Free Trial
Renews at €18.99p/m

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Keras Deep Learning Cookbook

Keras Installation

In this chapter, we will cover the following recipes:

  • Installing Keras on Ubuntu 16.04
  • Installing Keras with Jupyter Notebook in a Docker image
  • Installing Keras on Ubuntu 16.04 with GPU enabled

Introduction

In this chapter, we look at how Keras can be installed on Ubuntu and CentOS. We will use Ubuntu 16.04, 64-bit (Canonical, Ubuntu, 16.04 LTS, and amd64 xenial image build on 2017-10-26) for the installation.

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Key benefits

  • Understand different neural networks and their implementation using Keras
  • Explore recipes for training and fine-tuning your neural network models
  • Put your deep learning knowledge to practice with real-world use-cases, tips, and tricks

Description

Keras has quickly emerged as a popular deep learning library. Written in Python, it allows you to train convolutional as well as recurrent neural networks with speed and accuracy. The Keras Deep Learning Cookbook shows you how to tackle different problems encountered while training efficient deep learning models, with the help of the popular Keras library. Starting with installing and setting up Keras, the book demonstrates how you can perform deep learning with Keras in the TensorFlow. From loading data to fitting and evaluating your model for optimal performance, you will work through a step-by-step process to tackle every possible problem faced while training deep models. You will implement convolutional and recurrent neural networks, adversarial networks, and more with the help of this handy guide. In addition to this, you will learn how to train these models for real-world image and language processing tasks. By the end of this book, you will have a practical, hands-on understanding of how you can leverage the power of Python and Keras to perform effective deep learning

Who is this book for?

Keras Deep Learning Cookbook is for you if you are a data scientist or machine learning expert who wants to find practical solutions to common problems encountered while training deep learning models. A basic understanding of Python and some experience in machine learning and neural networks is required for this book.

What you will learn

  • Install and configure Keras in TensorFlow
  • Master neural network programming using the Keras library
  • Understand the different Keras layers
  • Use Keras to implement simple feed-forward neural networks, CNNs and RNNs
  • Work with various datasets and models used for image and text classification
  • Develop text summarization and reinforcement learning models using Keras

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : Oct 31, 2018
Length: 252 pages
Edition : 1st
Language : English
ISBN-13 : 9781788621755
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Google
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Product Details

Publication date : Oct 31, 2018
Length: 252 pages
Edition : 1st
Language : English
ISBN-13 : 9781788621755
Vendor :
Google
Category :
Languages :
Concepts :
Tools :

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Frequently bought together


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Table of Contents

11 Chapters
Keras Installation Chevron down icon Chevron up icon
Working with Keras Datasets and Models Chevron down icon Chevron up icon
Data Preprocessing, Optimization, and Visualization Chevron down icon Chevron up icon
Classification Using Different Keras Layers Chevron down icon Chevron up icon
Implementing Convolutional Neural Networks Chevron down icon Chevron up icon
Generative Adversarial Networks Chevron down icon Chevron up icon
Recurrent Neural Networks Chevron down icon Chevron up icon
Natural Language Processing Using Keras Models Chevron down icon Chevron up icon
Text Summarization Using Keras Models Chevron down icon Chevron up icon
Reinforcement Learning Chevron down icon Chevron up icon
Other Books You May Enjoy Chevron down icon Chevron up icon

Customer reviews

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(1 Ratings)
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1 star 100%
Anubhav Srivastava Nov 16, 2018
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Pretty much the worst book I have come across on this subject. There is literally no explanation of any of the code - this is just a massive dump of the author's Github. While I understand this is a "cookbook", you still need to explain some of the intricacies of the code. for e.g. why is the input share of LSTM different than say Dense layer? When do you want to use return_sequences=True or False? There is very little commentary on the logic behind why a certain code or variable is used.Very low effort work and super disappointing.
Amazon Verified review Amazon
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