Regression in Angular using TensorFlow.js
Regression in Angular using TensorFlow.js, Learn to build regression models to datasets using machine learning in Typescript.
Course Description
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!
