TensorFlow 2.0 Quick Start Guide: Get up to speed with the newly introduced features of TensorFlow 2.0 (English Edition)

Perform supervised and unsupervised machine learning and learn advanced techniques such as training neural networks

Key Features

Train your own models for effective prediction, using the high-level Keras API

Perform supervised and unsupervised machine learning and understand advanced techniques such as training neural networks

Get acquainted with the latest practices introduced in TensorFlow 2.0 Alpha

Book Description

TensorFlow is one of the most popular machine learning frameworks in Python. With this book, you'll get up to speed with some of the latest TensorFlow features, develop the skills you need to perform supervised and unsupervised machine learning, and even learn how to train neural networks.

You'll get started with an overview of what's new in TensorFlow 2.0 Alpha, before moving on to understanding how to set up your machine learning environment using the TensorFlow library. You'll then gain insights into performing popular supervised machine learning tasks using techniques such as linear regression, logistic regression, and clustering. Toward the later chapters, you will also get to grips with unsupervised learning for autoencoder applications. The book will finally guide you through training effective neural networks using practical examples in a variety of domains.

By the end of this book, you will have gained insights into a large variety of machine learning and neural network TensorFlow techniques, and be able to perform supervised and unsupervised machine learning with ease.

What you will learn

Use tf.keras for fast prototyping, building, and training deep learning neural network models

Convert your TensorFlow 1.12 applications to TensorFlow 2.0-compatible files

Use TensorFlow to tackle traditional supervised and unsupervised machine learning applications

Understand image recognition techniques using TensorFlow

Perform neural style transfer for image hybridization using a neural network

Code a recurrent neural network in TensorFlow to perform text-style generation

Who this book is for

This book is for data scientists, machine learning developers, and deep learning enthusiasts looking to quickly get started with TensorFlow 2. Some Python programming experience with version 3.6 or later, familiarity with Jupyter notebooks, and knowledge of machine learning and neural network techniques will be helpful to get the most out of this book.

Table of Contents

Introducing TensorFlow 2

Keras, a High-Level API for TensorFlow 2

ANN Technologies Using TensorFlow 2

Supervised Machine Learning Using TensorFlow 2

Unsupervised Learning Using TensorFlow 2

Recognizing Images with TensorFlow 2

Neural Style Transfer Using TensorFlow 2

Recurrent Neural Networks Using TensorFlow 2

TensorFlow Estimators and TensorFlow Hub

Converting from tf1.12 to tf2

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