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TensorFlow Machine Learning Cookbook

You're reading from   TensorFlow Machine Learning Cookbook Over 60 practical recipes to help you master Google's TensorFlow machine learning library

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Product type Paperback
Published in Feb 2017
Publisher Packt
ISBN-13 9781786462169
Length 370 pages
Edition 1st Edition
Languages
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Author (1):
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Nick McClure Nick McClure
Author Profile Icon Nick McClure
Nick McClure
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Toc

Table of Contents (13) Chapters Close

Preface 1. Getting Started with TensorFlow FREE CHAPTER 2. The TensorFlow Way 3. Linear Regression 4. Support Vector Machines 5. Nearest Neighbor Methods 6. Neural Networks 7. Natural Language Processing 8. Convolutional Neural Networks 9. Recurrent Neural Networks 10. Taking TensorFlow to Production 11. More with TensorFlow Index

Solving a System of ODEs


TensorFlow can be used for many algorithmic implementations and procedures. A great example of TensorFlow's versatility is implementing an ODE solver. Solving an ODE numerically is a iterative procedure that can be easily described in a computational graph. For this recipe, we will solve the Lotka-Volterra predator-prey system.

Getting ready

This recipe will illustrate how to solve a system of ordinary differential equations (ODEs). We can use similar methods to the previous two sections to update values as we iterate through and solve an ODE system.

The ODE system we will consider is the famous Lotka-Volterra predator-prey system. This system shows how a predator-prey system can be oscillating, given specific parameters.

The Lotka-Volterra system was published in a paper in 1920 (see also 1). We will use similar parameters to show that an oscillating system can occur. Here is the system represented in a mathematically discrete way:

Here, X is the prey and Y will be...

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