Search icon CANCEL
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
TensorFlow 2.0 Quick Start Guide
TensorFlow 2.0 Quick Start Guide

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

eBook
R$80 R$147.99
Paperback
R$183.99
Subscription
Free Trial
Renews at R$50p/m

What do you get with a Packt Subscription?

Free for first 7 days. $19.99 p/m after that. Cancel any time!
Product feature icon Unlimited ad-free access to the largest independent learning library in tech. Access this title and thousands more!
Product feature icon 50+ new titles added per month, including many first-to-market concepts and exclusive early access to books as they are being written.
Product feature icon Innovative learning tools, including AI book assistants, code context explainers, and text-to-speech.
Product feature icon Thousands of reference materials covering every tech concept you need to stay up to date.
Subscribe now
View plans & pricing
Table of content icon View table of contents Preview book icon Preview Book

TensorFlow 2.0 Quick Start Guide

Introducing TensorFlow 2

TensorFlow began its life in 2011 as DisBelief, an internal, closed source project at Google. DisBelief was a machine learning system that employed deep learning neural networks. This system morphed into TensorFlow, which was released to the developer community under an Apache 2.0 open source license, on November 9, 2015. Version 1.0.0 made its appearance on February 11, 2017. There have been a number of point releases since then that have incorporated a wealth of new features.

At the time of writing this book, the most recent version is TensorFlow 2.0.0 alpha release, which was announced at the TensorFlow Dev Summit on March 6, 2019.

TensorFlow takes its name from, well, tensors. A tensor is a generalization of vectors and matrices to possibly higher dimensions. The rank of a tensor is the number of indices it takes to uniquely specify each element of...

Looking at the modern TensorFlow ecosystem

Let's discuss eager execution. The first incarnation of TensorFlow involved constructing a computational graph made up of operations and tensors, which had to be subsequently evaluated in what Google termed as session (this is known as declarative programming). This is still a common way to write TensorFlow programs. However, eager execution, available from release 1.5 onward in research form and baked into TensorFlow proper from release 1.7, involves the immediate evaluation of operations, with the consequence that tensors can be treated like NumPy arrays (this is known as imperative programming).

Google says that eager execution is the preferred method for research and development but that computational graphs are to be preferred for serving TensorFlow production applications.

tf.data is an API that allows you to build complicated...

Installing TensorFlow

The best programming support for TensorFlow is provided for Python (although libraries do exist for Java, C, and Go, while those for other languages are under active development).

There is a wealth of information on the web for installing TensorFlow for Python.

It is standard practice, also recommended by Google, to install TensorFlow in a virtual environment, that is, an environment that isolates a set of APIs and code from other APIs and code and from the system-wide environment.

There are two distinct versions of TensorFlow—one for execution on a CPU and another for execution on a GPU. This last requires that the numerical libraries CUDA and CuDNN are installed. Tensorflow will default to GPU execution where possible. See https://www.tensorflow.org/alpha/guide/using_gpu.

Rather than attempt to reinvent the wheel here, there follow resources for...

Housekeeping and eager operations

We will first look at how to import TensorFlow, then TensorFlow coding style, and how to do some basic housekeeping. After this, we will look at some basic TensorFlow operations. You can either create a Jupyter Notebook for these snippets or use your favorite IDE to create your source code. The code is all available in the GitHub repository.

Importing TensorFlow

Importing TensorFlow is straightforward. Note a couple of system checks:

import tensorflow as tf
print("TensorFlow version: {}".format(tf.__version__))
print("Eager execution is: {}".format(tf.executing_eagerly()))
print("Keras version: {}".format(tf.keras.__version__))
...

Providing useful TensorFlow operations

Finding the squared difference between two tensors

Later in this book, we will need to find the square of the difference between two tensors. The method is as follows:

tf.math.squared.difference( x,  y, name=None)

Take the following example:

x = [1,3,5,7,11]
y = 5
s = tf.math.squared_difference(x,y)
s

The output will be as follows:

<tf...

Summary

In this chapter, we started to become familiar with TensorFlow by looking at a number of snippets of code illustrating some basic operations. We had a look at an overview of the modern TensorFlow ecosystem and how to install TensorFlow. We also examined some housekeeping operations, some eager operations, and a variety of TensorFlow operations that will be useful in the rest of this book. There is an excellent introduction to TensorFlow 2 at www.youtube.com/watch?v=k5c-vg4rjBw.

Also check out Appendix A for details of a tf1.12 to tf2 conversion tool. In the next chapter, we will take a look at Keras, which is a high-level API for TensorFlow 2.

Left arrow icon Right arrow icon
Download code icon Download Code

Key benefits

  • Train your own models for effective prediction, using high-level Keras API
  • Perform supervised and unsupervised machine learning and learn advanced techniques such as training neural networks
  • Get acquainted with some new practices introduced in TensorFlow 2.0 Alpha

Description

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

Who is this book for?

Data scientists, machine learning developers, and deep learning enthusiasts looking to quickly get started with TensorFlow 2 will find this book useful. Some Python programming experience with version 3.6 or later, along with a familiarity with Jupyter notebooks will be an added advantage. Exposure to machine learning and neural network techniques would also be helpful.

What you will learn

  • 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

Product Details

Country selected
Publication date, Length, Edition, Language, ISBN-13
Publication date : Mar 29, 2019
Length: 196 pages
Edition : 1st
Language : English
ISBN-13 : 9781789530759
Category :
Languages :
Tools :

What do you get with a Packt Subscription?

Free for first 7 days. $19.99 p/m after that. Cancel any time!
Product feature icon Unlimited ad-free access to the largest independent learning library in tech. Access this title and thousands more!
Product feature icon 50+ new titles added per month, including many first-to-market concepts and exclusive early access to books as they are being written.
Product feature icon Innovative learning tools, including AI book assistants, code context explainers, and text-to-speech.
Product feature icon Thousands of reference materials covering every tech concept you need to stay up to date.
Subscribe now
View plans & pricing

Product Details

Publication date : Mar 29, 2019
Length: 196 pages
Edition : 1st
Language : English
ISBN-13 : 9781789530759
Category :
Languages :
Tools :

Packt Subscriptions

See our plans and pricing
Modal Close icon
R$50 billed monthly
Feature tick icon Unlimited access to Packt's library of 7,000+ practical books and videos
Feature tick icon Constantly refreshed with 50+ new titles a month
Feature tick icon Exclusive Early access to books as they're written
Feature tick icon Solve problems while you work with advanced search and reference features
Feature tick icon Offline reading on the mobile app
Feature tick icon Simple pricing, no contract
R$500 billed annually
Feature tick icon Unlimited access to Packt's library of 7,000+ practical books and videos
Feature tick icon Constantly refreshed with 50+ new titles a month
Feature tick icon Exclusive Early access to books as they're written
Feature tick icon Solve problems while you work with advanced search and reference features
Feature tick icon Offline reading on the mobile app
Feature tick icon Choose a DRM-free eBook or Video every month to keep
Feature tick icon PLUS own as many other DRM-free eBooks or Videos as you like for just R$25 each
Feature tick icon Exclusive print discounts
R$800 billed in 18 months
Feature tick icon Unlimited access to Packt's library of 7,000+ practical books and videos
Feature tick icon Constantly refreshed with 50+ new titles a month
Feature tick icon Exclusive Early access to books as they're written
Feature tick icon Solve problems while you work with advanced search and reference features
Feature tick icon Offline reading on the mobile app
Feature tick icon Choose a DRM-free eBook or Video every month to keep
Feature tick icon PLUS own as many other DRM-free eBooks or Videos as you like for just R$25 each
Feature tick icon Exclusive print discounts

Frequently bought together


Stars icon
Total R$ 552.97
TensorFlow Machine Learning Projects
R$217.99
TensorFlow Reinforcement Learning Quick Start Guide
R$150.99
TensorFlow 2.0 Quick Start Guide
R$183.99
Total R$ 552.97 Stars icon

Table of Contents

14 Chapters
Section 1: Introduction to TensorFlow 2.00 Alpha Chevron down icon Chevron up icon
Introducing TensorFlow 2 Chevron down icon Chevron up icon
Keras, a High-Level API for TensorFlow 2 Chevron down icon Chevron up icon
ANN Technologies Using TensorFlow 2 Chevron down icon Chevron up icon
Section 2: Supervised and Unsupervised Learning in TensorFlow 2.00 Alpha Chevron down icon Chevron up icon
Supervised Machine Learning Using TensorFlow 2 Chevron down icon Chevron up icon
Unsupervised Learning Using TensorFlow 2 Chevron down icon Chevron up icon
Section 3: Neural Network Applications of TensorFlow 2.00 Alpha Chevron down icon Chevron up icon
Recognizing Images with TensorFlow 2 Chevron down icon Chevron up icon
Neural Style Transfer Using TensorFlow 2 Chevron down icon Chevron up icon
Recurrent Neural Networks Using TensorFlow 2 Chevron down icon Chevron up icon
TensorFlow Estimators and TensorFlow Hub Chevron down icon Chevron up icon
Converting from tf1.12 to tf2 Chevron down icon Chevron up icon
Other Books You May Enjoy Chevron down icon Chevron up icon

Customer reviews

Rating distribution
Full star icon Full star icon Half star icon Empty star icon Empty star icon 2.3
(3 Ratings)
5 star 33.3%
4 star 0%
3 star 0%
2 star 0%
1 star 66.7%
Amazon Kunde Aug 18, 2019
Full star icon Full star icon Full star icon Full star icon Full star icon 5
It's a great book with a lot of well explained examples. It starts with small simple examples and got more complex in the end. So you will get a good feeling how things work out in TensorFlow 2.0 .
Amazon Verified review Amazon
Yuhong Wang Jun 06, 2019
Full star icon Empty star icon Empty star icon Empty star icon Empty star icon 1
I got the kindle version, read the first a few chapters, and returned. As my title said, the tutorials from tensorflow.org and other web sites are more informational.
Amazon Verified review Amazon
Amazon Customer Apr 26, 2020
Full star icon Empty star icon Empty star icon Empty star icon Empty star icon 1
If you're familiar with TensorFlow already,and this book might be a guide to do a quick review on TF 2.0. Strongly not recommend to the user who is also new to TensorFlow... too many errors and also some code cannot run at all... I just follow the content of the book and still rely on TensorFlow official documents for coding part.... so not recommend it at all....
Amazon Verified review Amazon
Get free access to Packt library with over 7500+ books and video courses for 7 days!
Start Free Trial

FAQs

What is included in a Packt subscription? Chevron down icon Chevron up icon

A subscription provides you with full access to view all Packt and licnesed content online, this includes exclusive access to Early Access titles. Depending on the tier chosen you can also earn credits and discounts to use for owning content

How can I cancel my subscription? Chevron down icon Chevron up icon

To cancel your subscription with us simply go to the account page - found in the top right of the page or at https://subscription.packtpub.com/my-account/subscription - From here you will see the ‘cancel subscription’ button in the grey box with your subscription information in.

What are credits? Chevron down icon Chevron up icon

Credits can be earned from reading 40 section of any title within the payment cycle - a month starting from the day of subscription payment. You also earn a Credit every month if you subscribe to our annual or 18 month plans. Credits can be used to buy books DRM free, the same way that you would pay for a book. Your credits can be found in the subscription homepage - subscription.packtpub.com - clicking on ‘the my’ library dropdown and selecting ‘credits’.

What happens if an Early Access Course is cancelled? Chevron down icon Chevron up icon

Projects are rarely cancelled, but sometimes it's unavoidable. If an Early Access course is cancelled or excessively delayed, you can exchange your purchase for another course. For further details, please contact us here.

Where can I send feedback about an Early Access title? Chevron down icon Chevron up icon

If you have any feedback about the product you're reading, or Early Access in general, then please fill out a contact form here and we'll make sure the feedback gets to the right team. 

Can I download the code files for Early Access titles? Chevron down icon Chevron up icon

We try to ensure that all books in Early Access have code available to use, download, and fork on GitHub. This helps us be more agile in the development of the book, and helps keep the often changing code base of new versions and new technologies as up to date as possible. Unfortunately, however, there will be rare cases when it is not possible for us to have downloadable code samples available until publication.

When we publish the book, the code files will also be available to download from the Packt website.

How accurate is the publication date? Chevron down icon Chevron up icon

The publication date is as accurate as we can be at any point in the project. Unfortunately, delays can happen. Often those delays are out of our control, such as changes to the technology code base or delays in the tech release. We do our best to give you an accurate estimate of the publication date at any given time, and as more chapters are delivered, the more accurate the delivery date will become.

How will I know when new chapters are ready? Chevron down icon Chevron up icon

We'll let you know every time there has been an update to a course that you've bought in Early Access. You'll get an email to let you know there has been a new chapter, or a change to a previous chapter. The new chapters are automatically added to your account, so you can also check back there any time you're ready and download or read them online.

I am a Packt subscriber, do I get Early Access? Chevron down icon Chevron up icon

Yes, all Early Access content is fully available through your subscription. You will need to have a paid for or active trial subscription in order to access all titles.

How is Early Access delivered? Chevron down icon Chevron up icon

Early Access is currently only available as a PDF or through our online reader. As we make changes or add new chapters, the files in your Packt account will be updated so you can download them again or view them online immediately.

How do I buy Early Access content? Chevron down icon Chevron up icon

Early Access is a way of us getting our content to you quicker, but the method of buying the Early Access course is still the same. Just find the course you want to buy, go through the check-out steps, and you’ll get a confirmation email from us with information and a link to the relevant Early Access courses.

What is Early Access? Chevron down icon Chevron up icon

Keeping up to date with the latest technology is difficult; new versions, new frameworks, new techniques. This feature gives you a head-start to our content, as it's being created. With Early Access you'll receive each chapter as it's written, and get regular updates throughout the product's development, as well as the final course as soon as it's ready.We created Early Access as a means of giving you the information you need, as soon as it's available. As we go through the process of developing a course, 99% of it can be ready but we can't publish until that last 1% falls in to place. Early Access helps to unlock the potential of our content early, to help you start your learning when you need it most. You not only get access to every chapter as it's delivered, edited, and updated, but you'll also get the finalized, DRM-free product to download in any format you want when it's published. As a member of Packt, you'll also be eligible for our exclusive offers, including a free course every day, and discounts on new and popular titles.