Machine Learning in JavaScript with TensorFlowjs

Master machine learning with JavaScript and TensorFlowJS. Add artificial intelligence to websites, Node.js and web apps!
Machine Learning in JavaScript with TensorFlowjs
File Size :
2.15 GB
Total length :
7h 16m


Instructor team


Last update




Machine Learning in JavaScript with TensorFlowjs

What you’ll learn

Machine Learning in Javascript and TensorFlowJS 3
Deep Learning and Neural Network concepts
Why TensorFlow for JavaScript is a game changer
Defining machine learning models
How to install and run TensorFlowJS 3
How TensorFlowJS 3 is optimised
Training machine learning models
Data preparation for machine learning
How to make accurate predictions
Linear regression
Binary classification
Multi-class classification
Heatmap visualisation
Scatter-plot visualisation
Importing and normalising data
How to manage memory in TensorFlowJS 3
Tensor mathematics
Saving machine learning models
Inputting and outputting using a web browser
Javascript and machine learning integration
Shuffling, and splitting data
In-depth labs for practical development

Machine Learning in JavaScript with TensorFlowjs


Javascript basics
Some high school maths (but we give links if you need a refresher!)


Updated for 2022! Interested in using Machine Learning in JavaScript applications and websites? Then this course is for you!This is the tutorial you’ve been looking for to become a modern JavaScript machine learning master in 2022. It doesn’t just cover the basics, by the end of the course you will have advanced machine learning knowledge you can use on you resume. From absolute zero knowledge to master – join the TensorFlow.js revolution.This course has been designed by a specialist team of software developers who are passionate about using JavaScript with Machine Learning. We will guide you through complex topics in a practical way, and reinforce learning with in-depth labs and quizzes.Throughout the course we use house price data to ask ever more complicated questions; “can you predict the value of this house?”, “can you tell me if this house has a waterfront?”, “can you classify it as having 1, 2 or 3+ bedrooms?”. Each example builds on the one before it, to reinforce learning in easy and steady steps.Machine Learning in TensorFlow.js provides you with all the benefits of TensorFlow, but without the need for Python. This is demonstrated using web based examples, stunning visualisations and custom website components.This course is fun and engaging, with Machine Learning learning outcomes provided in bitesize topics:Part 1 – Introduction to TensorFlow.jsPart 2 – Installing and running TensorFlow.jsPart 3 – TensorFlow.js Core ConceptsPart 4 – Data Preparation with TensorFlow.jsPart 5 – Defining a modelPart 6 – Training and Testing in TensorFlow.jsPart 7 – TensorFlow.js PredictionPart 8 – Binary ClassificationPart 9 – Multi-class ClassificationPart 10 – Conclusion & Next StepsAs a bonus, for every student, we provide you with JavaScript and HTML code templates that you can download and use on your own projects.


Section 1: Introduction

Lecture 1 Introduction: What is TensorFlow.js?

Lecture 2 Course Overview

Lecture 3 Machine Learning Concepts

Lecture 4 Overview of Artificial Neural Networks

Lecture 5 Lab: TensorFlow Playground

Lecture 6 Summary

Section 2: Installing and running TensorFlow.js

Lecture 7 TensorFlow.js environments

Lecture 8 Running TensorFlow.js in the browser

Lecture 9 WebGL optimisations in TensorFlow.js

Lecture 10 Running TensorFlow.js on Node.js

Lecture 11 New: TensorFlow.js for React Native

Lecture 12 Review

Lecture 13 Lab: Install and run TensorFlow.js in the browser

Lecture 14 Lab: Install and run TensorFlow.js on Node.js

Lecture 15 Summary

Section 3: TensorFlow.js Core Concepts

Lecture 16 TensorFlow.js APIs

Lecture 17 What is a Tensor?

Lecture 18 Tensor Math Operations & Ops API

Lecture 19 Memory Management in TensorFlow.js

Lecture 20 Review

Lecture 21 Lab: Tensor Math and Memory Management

Lecture 22 Summary

Section 4: Data Preparation with TensorFlow.js

Lecture 23 Linear Regression

Lecture 24 Reading data from CSV

Lecture 25 Visualising the data

Lecture 26 Preparing Features and Labels

Lecture 27 Normalisation with TensorFlow.js

Lecture 28 Splitting into Training and Testing data

Lecture 29 Review

Lecture 30 Lab: Prepare the Data

Lecture 31 Summary

Section 5: Defining a model

Lecture 32 Introduction to Layers API

Lecture 33 Creating Layers in TensorFlow.js

Lecture 34 Inspecting a TensorFlow.js model

Lecture 35 Compiling the model

Lecture 36 Review

Lecture 37 Lab: Creating a Model

Lecture 38 Summary

Section 6: Training and Testing in TensorFlow.js

Lecture 39 Introduction to Training and Testing

Lecture 40 Training with

Lecture 41 Visualising loss with tfjs-vis

Lecture 42 Testing with model.evaluate

Lecture 43 Training and testing: review & lab

Lecture 44 Lab: TensorFlow.js Training and Testing

Lecture 45 Summary

Section 7: TensorFlow.js Prediction

Lecture 46 Integrating TensorFlow.js with a UI

Lecture 47 Saving and loading a model

Lecture 48 Making Predictions

Lecture 49 Visualising Predictions

Lecture 50 Non-linear Regression

Lecture 51 Prediction: review & labs

Lecture 52 Lab: TensorFlow.js predictions

Lecture 53 Lab: Beyond Linear Regression

Lecture 54 Lab (optional): Training without Layers API

Lecture 55 Summary

Section 8: Binary Classification

Lecture 56 Introduction: Binary Classification

Lecture 57 Visualising Classification Data

Lecture 58 Preparing Multiple Features

Lecture 59 Binary Classification Model

Lecture 60 Visualising Classification with Heatmaps

Lecture 61 Binary Classification Predictions

Lecture 62 Binary Classification: Review & Lab

Lecture 63 Lab: TensorFlow.js Binary Classification

Lecture 64 Summary

Section 9: Multi-class Classification

Lecture 65 Introduction: Multi-class Classification

Lecture 66 One hot encoding

Lecture 67 Multi-class classification model

Lecture 68 Visualising Multi-class Predictions

Lecture 69 Multi-class prediction

Lecture 70 Multi-class Classification: Review & Lab

Lecture 71 Lab: TensorFlow.js Multi-class Classification

Lecture 72 Summary

Section 10: Conclusion & Next Steps

Lecture 73 Course Review

Lecture 74 Next steps with TensorFlow.js

Lecture 75 Resources for going deeper with TensorFlow.js

Anyone who wants to start using machine learning in their apps and websites using Javascript

Course Information:

Udemy | English | 7h 16m | 2.15 GB
Created by: team

You Can See More Courses in the Developer >> Greetings from

New Courses

Scroll to Top