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

What is unsupervised learning?

As we mentioned previously, people often learn something without being given instructions to do so. They can find patterns by themselves and apply their own findings to the new observations naturally. This may be due to our creativity and our motivation to make meaningful progress in terms of the knowledge we seek. When we looked into machine learning algorithms, we learned that they need to be trained with a given target value. Due to this, you may have come to the assumption that computers don't learn anything unless they're provided with answers by a human.

Unsupervised learning is a type of machine learning problem that finds specific patterns spontaneously without getting the answers in the training phase. This sort of problem emerges not only when we don't have any clear answer to predict, but also when the purpose is not predicting...