Book Image

TensorFlow Machine Learning Cookbook - Second Edition

By : Nick McClure
Book Image

TensorFlow Machine Learning Cookbook - Second Edition

By: Nick McClure

Overview of this book

TensorFlow is an open source software library for Machine Intelligence. The independent recipes in this book will teach you how to use TensorFlow for complex data computations and allow you to dig deeper and gain more insights into your data than ever before. With the help of this book, you will work with recipes for training models, model evaluation, sentiment analysis, regression analysis, clustering analysis, artificial neural networks, and more. You will explore RNNs, CNNs, GANs, reinforcement learning, and capsule networks, each using Google's machine learning library, TensorFlow. Through real-world examples, you will get hands-on experience with linear regression techniques with TensorFlow. Once you are familiar and comfortable with the TensorFlow ecosystem, you will be shown how to take it to production. By the end of the book, you will be proficient in the field of machine intelligence using TensorFlow. You will also have good insight into deep learning and be capable of implementing machine learning algorithms in real-world scenarios.
Table of Contents (13 chapters)

Solving a system of ordinary differential equations

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 an 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...