Book description
Get handson with the browserbased JavaScript library for training and deploying machine learning models effectively
Key Features
 Build, train and run machine learning models in the browser using TensorFlow.js
 Create smart web applications from scratch with the help of useful examples
 Use flexible and intuitive APIs from TensorFlow.js to understand how machine learning algorithms function
Book Description
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 examplebased 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 MLbased 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 webbased ML applications and finetune models to achieve high performance.
What you will learn
 Use the tSNE algorithm in TensorFlow.js to reduce dimensions in an input dataset
 Deploy tfjsconverter to convert Keras models and load them into TensorFlow.js
 Apply the Bellman equation to solve MDP problems
 Use the kmeans algorithm in TensorFlow.js to visualize prediction results
 Create tf.js packages with Parcel, Webpack, and Rollup to deploy web apps
 Implement tf.js backend frameworks to tune and accelerate app performance
Who this book is for
This book is for web developers who want to learn how to integrate machine learning techniques with webbased applications from scratch. This book will also appeal to data scientists, machine learning practitioners, and deep learning enthusiasts who are looking to perform accelerated, browserbased machine learning on Web using TensorFlow.js. Working knowledge of JavaScript programming language is all you need to get started.
Publisher resources
Table of contents
 Title Page
 Copyright and Credits
 About Packt
 Contributors
 Preface
 Section 1: The Rationale of Machine Learning and the Usage of TensorFlow.js
 Machine Learning for the Web
 Importing Pretrained Models into TensorFlow.js
 TensorFlow.js Ecosystem
 Section 2: RealWorld Applications of TensorFlow.js
 Polynomial Regression
 Classification with Logistic Regression
 Unsupervised Learning
 Sequential Data Analysis
 Dimensionality Reduction
 Solving the Markov Decision Process
 Section 3: Productionizing Machine Learning Applications with TensorFlow.js
 Deploying Machine Learning Applications
 Tuning Applications to Achieve High Performance

Future Work Around TensorFlow.js
 Technical requirements
 Experimental backend implementations
 AutoML edge helper
 Summary
 Questions
 Further Reading
 Other Books You May Enjoy
Product information
 Title: HandsOn Machine Learning with TensorFlow.js
 Author(s):
 Release date: November 2019
 Publisher(s): Packt Publishing
 ISBN: 9781838821739
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