TensorFlow 2.0 Quick Start Guide

TensorFlow 2.0 Quick Start Guide

eBook Details:

  • Paperback: 196 pages
  • Publisher: WOW! eBook (March 29, 2019)
  • Language: English
  • ISBN-10: 178953075X
  • ISBN-13: 978-1789530759

eBook Description:

TensorFlow 2.0 Quick Start Guide: Perform supervised and unsupervised machine learning and learn advanced techniques such as training neural networks

TensorFlow is one of the most popular machine learning frameworks in Python. With this book, you will improve your knowledge of some of the latest TensorFlow features and will be able to perform supervised and unsupervised machine learning and also train neural networks.

After giving you an overview of what’s new in TensorFlow 2.0 Alpha, the book moves on to setting up your machine learning environment using the TensorFlow library. You will perform popular supervised machine learning tasks using techniques such as linear regression, logistic regression, and clustering.

You will get familiar with unsupervised learning for autoencoder applications. The book will also show you how to train effective neural networks using straightforward examples in a variety of different domains.

  • Use tf.Keras for fast prototyping, building, and training deep learning neural network models
  • Easily 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

By the end of the TensorFlow 2.0 Quick Start Guide book, you will have been exposed to a large variety of machine learning and neural network TensorFlow techniques.

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1 Response

  1. April 19, 2020

    […] datasets, and then deploy these models to production. All the code presented in the Learn TensorFlow 2.0 book will be available in the form of executable scripts at Github which allows you to try out the […]

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