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TensorFlow 2.0 Quick Start Guide

TensorFlow 2.0 Quick Start Guide

By : Holdroyd
2.3 (3)
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TensorFlow 2.0 Quick Start Guide

TensorFlow 2.0 Quick Start Guide

2.3 (3)
By: Holdroyd

Overview of this book

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.
Table of Contents (15 chapters)
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1
Section 1: Introduction to TensorFlow 2.00 Alpha
5
Section 2: Supervised and Unsupervised Learning in TensorFlow 2.00 Alpha
7
Unsupervised Learning Using TensorFlow 2
8
Section 3: Neural Network Applications of TensorFlow 2.00 Alpha
13
Converting from tf1.12 to tf2

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...
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