Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Save more on your purchases! discount-offer-chevron-icon
Savings automatically calculated. No voucher code required.
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Newsletter Hub
Free Learning
Arrow right icon
timer SALE ENDS IN
0 Days
:
00 Hours
:
00 Minutes
:
00 Seconds
The TensorFlow Workshop
The TensorFlow Workshop

The TensorFlow Workshop: A hands-on guide to building deep learning models from scratch using real-world datasets

Arrow left icon
Profile Icon Matthew Moocarme Profile Icon Abhranshu Bagchi Profile Icon Anthony So Profile Icon Maddalone
Arrow right icon
Can$39.99 Can$44.99
Full star icon Full star icon Full star icon Full star icon Half star icon 4.6 (25 Ratings)
eBook Dec 2021 600 pages 1st Edition
eBook
Can$39.99 Can$44.99
Paperback
Can$55.99
Subscription
Free Trial
Arrow left icon
Profile Icon Matthew Moocarme Profile Icon Abhranshu Bagchi Profile Icon Anthony So Profile Icon Maddalone
Arrow right icon
Can$39.99 Can$44.99
Full star icon Full star icon Full star icon Full star icon Half star icon 4.6 (25 Ratings)
eBook Dec 2021 600 pages 1st Edition
eBook
Can$39.99 Can$44.99
Paperback
Can$55.99
Subscription
Free Trial
eBook
Can$39.99 Can$44.99
Paperback
Can$55.99
Subscription
Free Trial

What do you get with eBook?

Product feature icon Instant access to your Digital eBook purchase
Product feature icon Download this book in EPUB and PDF formats
Product feature icon Access this title in our online reader with advanced features
Product feature icon DRM FREE - Read whenever, wherever and however you want
Product feature icon AI Assistant (beta) to help accelerate your learning
OR
Modal Close icon
Payment Processing...
tick Completed

Billing Address

Table of content icon View table of contents Preview book icon Preview Book

The TensorFlow Workshop

2. Loading and Processing Data

Overview

In this chapter, you will learn how to load and process a variety of data types for modeling in TensorFlow. You will implement methods to input data into TensorFlow models so that model training can be optimized.

By the end of this chapter, you will know how to input tabular data, images, text, and audio data and preprocess them so that they are suitable for training TensorFlow models.

Introduction

In the previous chapter, you learned how to create, utilize, and apply linear transformations to tensors using TensorFlow. The chapter started with the definition of tensors and how they can be created using the Variable class in the TensorFlow library. You then created tensors of various ranks and learned how to apply tensor addition, reshaping, transposition, and multiplication using the library. These are all examples of linear transformations. You concluded that chapter by covering optimization methods and activation functions and how they can be accessed in the TensorFlow library.

When training machine learning models in TensorFlow, you must supply the model with training data. The raw data that is available may come in a variety of formats—for example, tabular CSV files, images, audio, or text files. Different data sources are loaded and preprocessed in different ways in order to provide numerical tensors for TensorFlow models. For example, virtual assistants use voice queries as input interaction and then apply machine learning models to decipher input speech and perform specific actions as output. To create the models for this task, the audio data of the speech input must be loaded into memory. A preprocessing step also needs to be involved that converts the audio input into text. Following this, the text is converted into numerical tensors for model training. This is one example that demonstrates the complexity of creating models from non-tabular, non-numerical data such as audio data.

This chapter will explore a few of the common data types that are utilized for building machine learning models. You will load raw data into memory in an efficient manner, and then perform some preprocessing steps to convert the raw data into numerical tensors that are appropriate for training machine learning models. Luckily, machine learning libraries have advanced significantly, which means that training models with data types such as images, text, and audio is extremely accessible to practitioners.

Left arrow icon Right arrow icon
Download code icon Download Code

Key benefits

  • Understand the fundamentals of tensors, neural networks, and deep learning
  • Discover how to implement and fine-tune deep learning models for real-world datasets
  • Build your experience and confidence with hands-on exercises and activities

Description

Getting to grips with tensors, deep learning, and neural networks can be intimidating and confusing for anyone, no matter their experience level. The breadth of information out there, often written at a very high level and aimed at advanced practitioners, can make getting started even more challenging. If this sounds familiar to you, The TensorFlow Workshop is here to help. Combining clear explanations, realistic examples, and plenty of hands-on practice, it’ll quickly get you up and running. You’ll start off with the basics – learning how to load data into TensorFlow, perform tensor operations, and utilize common optimizers and activation functions. As you progress, you’ll experiment with different TensorFlow development tools, including TensorBoard, TensorFlow Hub, and Google Colab, before moving on to solve regression and classification problems with sequential models. Building on this solid foundation, you’ll learn how to tune models and work with different types of neural network, getting hands-on with real-world deep learning applications such as text encoding, temperature forecasting, image augmentation, and audio processing. By the end of this deep learning book, you’ll have the skills, knowledge, and confidence to tackle your own ambitious deep learning projects with TensorFlow.

Who is this book for?

This TensorFlow book is for anyone who wants to develop their understanding of deep learning and get started building neural networks with TensorFlow. Basic knowledge of Python programming and its libraries, as well as a general understanding of the fundamentals of data science and machine learning, will help you grasp the topics covered in this book more easily.

What you will learn

  • Get to grips with TensorFlow's mathematical operations
  • Pre-process a wide variety of tabular, sequential, and image data
  • Understand the purpose and usage of different deep learning layers
  • Perform hyperparameter-tuning to prevent overfitting of training data
  • Use pre-trained models to speed up the development of learning models
  • Generate new data based on existing patterns using generative models

Product Details

Country selected
Publication date, Length, Edition, Language, ISBN-13
Publication date : Dec 15, 2021
Length: 600 pages
Edition : 1st
Language : English
ISBN-13 : 9781800200227
Category :
Languages :
Concepts :

What do you get with eBook?

Product feature icon Instant access to your Digital eBook purchase
Product feature icon Download this book in EPUB and PDF formats
Product feature icon Access this title in our online reader with advanced features
Product feature icon DRM FREE - Read whenever, wherever and however you want
Product feature icon AI Assistant (beta) to help accelerate your learning
OR
Modal Close icon
Payment Processing...
tick Completed

Billing Address

Product Details

Publication date : Dec 15, 2021
Length: 600 pages
Edition : 1st
Language : English
ISBN-13 : 9781800200227
Category :
Languages :
Concepts :

Packt Subscriptions

See our plans and pricing
Modal Close icon
$19.99 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
$199.99 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 Can$6 each
Feature tick icon Exclusive print discounts
$279.99 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 Can$6 each
Feature tick icon Exclusive print discounts

Frequently bought together


Stars icon
Total Can$ 199.97
Machine Learning for Time-Series with Python
Can$69.99
Machine Learning for Algorithmic Trading
Can$73.99
The TensorFlow Workshop
Can$55.99
Total Can$ 199.97 Stars icon

Table of Contents

11 Chapters
1. Introduction to Machine Learning with TensorFlow Chevron down icon Chevron up icon
2. Loading and Processing Data Chevron down icon Chevron up icon
3. TensorFlow Development Chevron down icon Chevron up icon
4. Regression and Classification Models Chevron down icon Chevron up icon
5. Classification Models Chevron down icon Chevron up icon
6. Regularization and Hyperparameter Tuning Chevron down icon Chevron up icon
7. Convolutional Neural Networks Chevron down icon Chevron up icon
8. Pre-Trained Networks Chevron down icon Chevron up icon
9. Recurrent Neural Networks Chevron down icon Chevron up icon
10. Custom TensorFlow Components Chevron down icon Chevron up icon
11. Generative Models Chevron down icon Chevron up icon

Customer reviews

Top Reviews
Rating distribution
Full star icon Full star icon Full star icon Full star icon Half star icon 4.6
(25 Ratings)
5 star 64%
4 star 28%
3 star 8%
2 star 0%
1 star 0%
Filter icon Filter
Top Reviews

Filter reviews by




Atalay Denknalbant Dec 19, 2021
Full star icon Full star icon Full star icon Full star icon Full star icon 5
In this book, there are decent explanations of neural network models and case studies based on those models which are tailor-made and help to understand models easily. Additionally, also book touches on every necessary TensorFlow class that widens readers' TensorFlow knowledge.
Amazon Verified review Amazon
Dwayne M Feb 16, 2022
Full star icon Full star icon Full star icon Full star icon Full star icon 5
This book provides an in-depth perspective on all things TensorFlow from preprocessing to output. You learn how to avoid many mistakes that can cost valuable time and how to structure your models for optimal prediction accuracy and success. You will also learn about important topics such as transfer learning and custom components. I only wish this book covered deployment in greater detail.
Amazon Verified review Amazon
Dillon Grafton Feb 21, 2022
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Awesome presentation with concise easy to follow chapters. Great book!
Amazon Verified review Amazon
Ercim Caglasan Feb 08, 2022
Full star icon Full star icon Full star icon Full star icon Full star icon 5
It has lots of insights and in depth knowledge of ML and deep learning consepts as well as well structured step by step hands on practical guides through tensorFlow framework. It covers all the basic algorithms and also covers important developments like nlp, transfer learning, optimization techniques and model measurements.It gives you ways to generate end to end pipeline from gathering and cleaning data and to building models and deployment. Although I would like to have more information on model developments in real production environments, this may come in the second edition :)Anyhow, good job on putting this all together.👍🏻
Amazon Verified review Amazon
Rustem Dec 21, 2021
Full star icon Full star icon Full star icon Full star icon Full star icon 5
The book covers DL model architecture using Tensorflow with code examples. It would be useful for beginners but also as a reference for data scientists and ML engineers. Keep in mind that it is specifically focused on building neural networks and not on training or inference. Regarding network components, it covers most contemporary architectures though it doesn't cover transformers.
Amazon Verified review Amazon
Get free access to Packt library with over 7500+ books and video courses for 7 days!
Start Free Trial

FAQs

How do I buy and download an eBook? Chevron down icon Chevron up icon

Where there is an eBook version of a title available, you can buy it from the book details for that title. Add either the standalone eBook or the eBook and print book bundle to your shopping cart. Your eBook will show in your cart as a product on its own. After completing checkout and payment in the normal way, you will receive your receipt on the screen containing a link to a personalised PDF download file. This link will remain active for 30 days. You can download backup copies of the file by logging in to your account at any time.

If you already have Adobe reader installed, then clicking on the link will download and open the PDF file directly. If you don't, then save the PDF file on your machine and download the Reader to view it.

Please Note: Packt eBooks are non-returnable and non-refundable.

Packt eBook and Licensing When you buy an eBook from Packt Publishing, completing your purchase means you accept the terms of our licence agreement. Please read the full text of the agreement. In it we have tried to balance the need for the ebook to be usable for you the reader with our needs to protect the rights of us as Publishers and of our authors. In summary, the agreement says:

  • You may make copies of your eBook for your own use onto any machine
  • You may not pass copies of the eBook on to anyone else
How can I make a purchase on your website? Chevron down icon Chevron up icon

If you want to purchase a video course, eBook or Bundle (Print+eBook) please follow below steps:

  1. Register on our website using your email address and the password.
  2. Search for the title by name or ISBN using the search option.
  3. Select the title you want to purchase.
  4. Choose the format you wish to purchase the title in; if you order the Print Book, you get a free eBook copy of the same title. 
  5. Proceed with the checkout process (payment to be made using Credit Card, Debit Cart, or PayPal)
Where can I access support around an eBook? Chevron down icon Chevron up icon
  • If you experience a problem with using or installing Adobe Reader, the contact Adobe directly.
  • To view the errata for the book, see www.packtpub.com/support and view the pages for the title you have.
  • To view your account details or to download a new copy of the book go to www.packtpub.com/account
  • To contact us directly if a problem is not resolved, use www.packtpub.com/contact-us
What eBook formats do Packt support? Chevron down icon Chevron up icon

Our eBooks are currently available in a variety of formats such as PDF and ePubs. In the future, this may well change with trends and development in technology, but please note that our PDFs are not Adobe eBook Reader format, which has greater restrictions on security.

You will need to use Adobe Reader v9 or later in order to read Packt's PDF eBooks.

What are the benefits of eBooks? Chevron down icon Chevron up icon
  • You can get the information you need immediately
  • You can easily take them with you on a laptop
  • You can download them an unlimited number of times
  • You can print them out
  • They are copy-paste enabled
  • They are searchable
  • There is no password protection
  • They are lower price than print
  • They save resources and space
What is an eBook? Chevron down icon Chevron up icon

Packt eBooks are a complete electronic version of the print edition, available in PDF and ePub formats. Every piece of content down to the page numbering is the same. Because we save the costs of printing and shipping the book to you, we are able to offer eBooks at a lower cost than print editions.

When you have purchased an eBook, simply login to your account and click on the link in Your Download Area. We recommend you saving the file to your hard drive before opening it.

For optimal viewing of our eBooks, we recommend you download and install the free Adobe Reader version 9.