Book Image

Hands-On Machine Learning with TensorFlow.js

By : Kai Sasaki
Book Image

Hands-On Machine Learning with TensorFlow.js

By: Kai Sasaki

Overview of this book

TensorFlow.js is a framework that enables you to create performant machine learning (ML) applications that run smoothly in a web browser. With this book, you will learn how to use TensorFlow.js to implement various ML models through an example-based approach. Starting with the basics, you'll understand how ML models can be built on the web. Moving on, you will get to grips with the TensorFlow.js ecosystem to develop applications more efficiently. The book will then guide you through implementing ML techniques and algorithms such as regression, clustering, fast Fourier transform (FFT), and dimensionality reduction. You will later cover the Bellman equation to solve Markov decision process (MDP) problems and understand how it is related to reinforcement learning. Finally, you will explore techniques for deploying ML-based web applications and training models with TensorFlow Core. Throughout this ML book, you'll discover useful tips and tricks that will build on your knowledge. By the end of this book, you will be equipped with the skills you need to create your own web-based ML applications and fine-tune models to achieve high performance.
Table of Contents (17 chapters)
Free Chapter
1
Section 1: The Rationale of Machine Learning and the Usage of TensorFlow.js
5
Section 2: Real-World Applications of TensorFlow.js
12
Section 3: Productionizing Machine Learning Applications with TensorFlow.js

Deploying Machine Learning Applications

There are several ways in which we can deploy web applications. We need to be familiar with the common frameworks that pack up our artifacts and machine learning models. In this chapter, we are going to learn how to create a package of TensorFlow.js applications. In the previous chapters, we have written various kinds of machine learning applications using TensorFlow.js. These applications are so simple that it would be great to learn about the basic building blocks that we use when we write an application with TensorFlow.js. But this is just the beginning.

From this chapter onward, more advanced topics will be covered. Therefore, it would be useful to make our applications production-ready in terms of performance and portability.

In this chapter, we will cover the following topics:

  • The ecosystem around the JavaScript platform
  • Module bundler...