Regression in Angular using TensorFlow.js

Learn to build regression models for datasets using machine learning in Typescript


Data Science is all about finding information/knowledge from datasets. One very powerful approach is using linear models, called regression. Even though they are limited, they still can delivery something if the datasets have a linear tendency.

On this course, we use Angular as framework, coding environment, and TensorFlow.js as the library for creating a machine learning based regression model.

What is Angular??

Angular is a framework, designed by the Google Team, and it has been widely used to design sites.Essentially, it is a framework to create frontends, based on TypeScript. In layman’s terms: the page you see and interact on your web browser.

It is a framework to create frontends.

What is TensoFlow.js??

TensorFlow.js is a JavaScript-based library for deep learning, based on the classical TensorFlow, written in Python; you can also do simple learning machine, some simple mathematical operations with tensors and so on. There are several reasons for using TensorFlow.js instead of Python, and I hope to come back to that in the future.

A nice point is that they claim it is possible to transform models in both directions: TensorFlow.js <-> TensorFlow.

We are going to build a linear regression model using TensorFlow.js in Angular. We are also going to learn about machine learning, and Angular!

Who this course is for:

  • JavaScript programmers waiting to learng machine learning
  • Machine learning practitioners wanting to learn web coding
  • Angular coders wanting to add intelligence to their apps

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