Search icon CANCEL
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
The Applied Artificial Intelligence Workshop

You're reading from   The Applied Artificial Intelligence Workshop Start working with AI today, to build games, design decision trees, and train your own machine learning models

Arrow left icon
Product type Paperback
Published in Jul 2020
Publisher Packt
ISBN-13 9781800205819
Length 420 pages
Edition 1st Edition
Languages
Tools
Arrow right icon
Authors (3):
Arrow left icon
Anthony So Anthony So
Author Profile Icon Anthony So
Anthony So
Zsolt Nagy Zsolt Nagy
Author Profile Icon Zsolt Nagy
Zsolt Nagy
William So William So
Author Profile Icon William So
William So
Arrow right icon
View More author details
Toc

Table of Contents (8) Chapters Close

Preface
1. Introduction to Artificial Intelligence 2. An Introduction to Regression FREE CHAPTER 3. An Introduction to Classification 4. An Introduction to Decision Trees 5. Artificial Intelligence: Clustering 6. Neural Networks and Deep Learning Appendix

Neurons in TensorFlow

TensorFlow is currently the most popular neural network and deep learning framework. It was created and is maintained by Google. TensorFlow is used for voice recognition and voice search, and it is also the brain behind translate.google.com. Later in this chapter, we will use TensorFlow to recognize written characters.

The TensorFlow API is available in many languages, including Python, JavaScript, Java, and C. TensorFlow works with tensors. You can think of a tensor as a container composed of a matrix (usually with high dimensions) and additional information related to the operations it will perform (such as weights and biases, which you will be looking at later in this chapter). A tensor with no dimensions (with no rank) is a scalar. A tensor of rank 1 is a vector, rank 2 tensors are matrices, and a rank 3 tensor is a three-dimensional matrix. The rank indicates the dimensions of a tensor. In this chapter, we will be looking at tensors of ranks 2 and...

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at €18.99/month. Cancel anytime