Deep Learning with TensorFlow 2 and Keras: Regression, ConvNets, GANs, RNNs, NLP, and more with TensorFlow 2 and the Keras API, 2nd Edition (English Edition)

Deep Learning with TensorFlow 2 and Keras: Regression, ConvNets, GANs, RNNs, NLP, and more with TensorFlow 2 and the Keras API, 2nd Edition (English Edition)

作者
Antonio Gulli、Amita Kapoor、Sujit Pal
语言
英语
出版社
Packt Publishing 版次:2
出版日期
2019年12月27日
纸书页数
648页
电子书格式
epub,pdf,mobi,azw3,txt,fb2,djvu
文件大小
28311 KB
下载次数
8601
更新日期
2023-06-09
运行环境
PC/Windows/Linux/Mac/IOS/iPhone/iPad/iBooks/Kindle/Android/安卓/平板
内容简介

Build machine and deep learning systems with the newly released TensorFlow 2 and Keras for the lab, production, and mobile devices

Key Features

Introduces and then uses TensorFlow 2 and Keras right from the start

Teaches key machine and deep learning techniques

Understand the fundamentals of deep learning and machine learning through clear explanations and extensive code samples

Book Description

Deep Learning with TensorFlow 2 and Keras, Second Edition teaches neural networks and deep learning techniques alongside TensorFlow (TF) and Keras. You’ll learn how to write deep learning applications in the most powerful, popular, and scalable machine learning stack available.

TensorFlow is the machine learning library of choice for professional applications, while Keras offers a simple and powerful Python API for accessing TensorFlow. TensorFlow 2 provides full Keras integration, making advanced machine learning easier and more convenient than ever before.

This book also introduces neural networks with TensorFlow, runs through the main applications (regression, ConvNets (CNNs), GANs, RNNs, NLP), covers two working example apps, and then dives into TF in production, TF mobile, and using TensorFlow with AutoML.

What you will learn

Build machine learning and deep learning systems with TensorFlow 2 and the Keras API

Use Regression analysis, the most popular approach to machine learning

Understand ConvNets (convolutional neural networks) and how they are essential for deep learning systems such as image classifiers

Use GANs (generative adversarial networks) to create new data that fits with existing patterns

Discover RNNs (recurrent neural networks) that can process sequences of input intelligently, using one part of a sequence to correctly interpret another

Apply deep learning to natural human language and interpret natural language texts to produce an appropriate response

Train your models on the cloud and put TF to work in real environments

Explore how Google tools can automate simple ML workflows without the need for complex modeling

Who this book is for

This book is for Python developers and data scientists who want to build machine learning and deep learning systems with TensorFlow. This book gives you the theory and practice required to use Keras, TensorFlow 2, and AutoML to build machine learning systems. Some knowledge of machine learning is expected. Table of Contents

Neural Network Foundations with TensorFlow 2.0

TensorFlow 1.x and 2.x

Regression

Convolutional Neural Networks

Advanced Convolutional Neural Networks

Generative Adversarial Networks

Word Embeddings

Recurrent Neural Networks

Autoencoders

Unsupervised Learning

Reinforcement Learning

TensorFlow and Cloud

TensorFlow for Mobile and IoT and TensorFlow.js

An introduction to AutoML

The Math Behind Deep Learning

Tensor Processing Unit

Deep Learning with TensorFlow 2 and Keras: Regression, ConvNets, GANs, RNNs, NLP, and more with TensorFlow 2 and the Keras API, 2nd Edition (English Edition) EPUB, PDF, MOBI, AZW3, TXT, FB2, DjVu, Kindle电子书免费下载。

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