This book aims to act as a comprehensive guide to help you implement machine learning applications using TensorFlow.js. Thus far, we have looked at the basics of the web platform and an overview of TensorFlow.js. Although further knowledge and building blocks to implement a machine learning application will be introduced later, what you've learned so far will be the basis for that.
From this chapter onward, we are going to implement real machine learning applications using TensorFlow.js. In this chapter, we are going to discuss how to implement a simple polynomial regression model with TensorFlow.js. You will learn about the basic building blocks of machine learning applications, such as the optimizer and the loss function to be optimized, and how they are used in the TensorFlow.js platform. To do this, we will implement a polynomial regression model...
