Go Pro!Bootcamp

Bootcamp

Study group

Collaborate with peers in your dedicated #study-group channel.

Code reviews

Submit projects for review using the /review command in your #code-reviews channel

Neural Networks in JavaScript

Enroll for freeGet started!

Join 8357 other students

Log in to get

Access to all our free courses
Interactive hands-on content
100s of code challenges
Join a friendly community
Enroll for free
Subscribe to access!Subscribe to access!

Subscribe to access to this course and ALL other courses. You get a 30-day money-back guarantee, no questions asked.

Subscription includes

All courses and career paths
100s of coding challenges
Certificates of completion
Exclusive Pro members chat
The course creator Robert Plummer

with Robert Plummer

Course level: Intermediate

A fun and practical Brain.js tutorial. This 19-part course teaches you how to build neural networks in JavaScript through interactive Scrimba tutorials.

You'll learn

Neural Network basics

How Neural Nets learn

Propagation

Structure

Layers

Objects

Normalization

Predicting steps

Recurrent Neural Net

Sentiment analysis

man

Prerequisites

Before taking this course, you should have a basic understanding of JavaScript. Here’s our suggested resource to get you up to speed.

Meet your teacher

The course creator

Robert Plummer

Follow me on twitter

Why this course rocks

This course gives you a practical introduction to Brain.js, a popular JavaScript library for building neural networks in the browser and in Node.js. And since this is Scrimba, you'll be able to interact with the neural networks whenever you want. Simply pause the screencast, edit the code and run the network with your own changes applied. Learning machine learning has never been as interactive as this!

What you'll learn

By the end of the course, you'll be able to solve a range of different problems using neural networks. The lectures does not dwell with much theory, but rather on how to code the networks. That means the course is suitable for anybody who knows JavaScript.

Good luck, and welcome to the exciting world of neural networks!

Join the Scrimba community chat

Learning alone can be lonely. Click here to join our Discord server and connect with other Scrimba learners!

F to the A oracle to the Q
Are neural networks machine learning?

Neural networks are a specific set of algorithms within machine learning. They are inspired by biological neural networks and the current so-called deep neural networks and have proven to work quite well.

What are neural networks and deep learning?

Neural networks are biologically-inspired programming concept which enables a computer to learn from observational data. Deep learning is a set of techniques for learning in neural networks.

What can neural networks do?

In short, neural networks can be used for solving business problems such as forecasting, customer research, data validation, and risk management. A more fun use could be to teach a neural network to play Mario cart.

What are the major benefits of neural networks?

Ability to learn and model non-linear and complex relationships, which is really important because in real-life, many of the relationships between inputs and outputs are non-linear as well as complex.