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Keras Deep Learning Cookbook
By :
Keras Deep Learning Cookbook
By:
Overview of this book
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
Table of Contents (12 chapters)
Preface
Free Chapter
Keras Installation
Working with Keras Datasets and Models
Data Preprocessing, Optimization, and Visualization
Classification Using Different Keras Layers
Implementing Convolutional Neural Networks
Generative Adversarial Networks
Recurrent Neural Networks
Natural Language Processing Using Keras Models
Text Summarization Using Keras Models
Reinforcement Learning
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