Machine Learning in JavaScript with TensorFlow.js
Machine Learning in JavaScript with TensorFlow.js
Master machine learning with JavaScript and TensorFlowJS. Add artificial intelligence to websites, Node.js and web apps!
Created by tech.courses team, Justin Emery | 6.5 hours on-demand video course
Updated for 2020! 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 2020. 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.
What you’ll learn
- Machine Learning in Javascript and TensorFlowJS
- Deep Learning and Neural Network concepts
- Why TensorFlow for JavaScript is a game changer
- Defining machine learning models
- How to install and run TensorFlowJS
- How TensorFlowJS 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
- 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
Recommended Course
