Machine Learning in JavaScript with TensorFlow.js
What you'll learn
- Machine Learning in Javascript and TensorFlowJS 4
- Deep Learning and Neural Network concepts
- Why TensorFlow for JavaScript is a game changer
- Defining machine learning models
- How to install and run TensorFlowJS 4
- How TensorFlowJS 4 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 4
- 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
Requirements
- Javascript basics
- Some high school maths (but we give links if you need a refresher!)
Description
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 2024. 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.js
Part 2 - Installing and running TensorFlow.js
Part 3 - TensorFlow.js Core Concepts
Part 4 - Data Preparation with TensorFlow.js
Part 5 - Defining a model
Part 6 - Training and Testing in TensorFlow.js
Part 7 - TensorFlow.js Prediction
Part 8 - Binary Classification
Part 9 - Multi-class Classification
Part 10 - Conclusion & Next Steps
As a bonus, for every student, we provide you with JavaScript and HTML code templates that you can download and use on your own projects.
Who this course is for:
- Anyone who wants to start using machine learning in their apps and websites using Javascript
Instructors
- 4.3 Instructor Rating
- 794 Reviews
- 5,736 Students
- 1 Course
Welcome to the tech.courses community, we look forward to providing massive value to you as you learn-by-doing with the best courses and instructors in the world.
Our courses cover state-of-the-art technology and software development topics. All instructors are experienced industry professionals who want to share their expertise!
See you inside,
John, Managing Director
- 4.3 Instructor Rating
- 794 Reviews
- 5,736 Students
- 1 Course
Professional Experience
I have been working as a software developer since 2007. I started out at Feral Interactive, a Mac & Linux video game publisher, building information systems to support all areas of the company. From 2011, I led a team responsible for online services, internal information systems, and the public website. I led development of Calico, an online multiplayer gaming platform.
Since 2017, I have been working freelance on a range of software development and technical consulting projects for startups, from backend APIs to support mobile apps, to a chatbot utilising state-of-the-art machine learning techniques.
Education
I've always looked to invest in the best education.
I graduated with 1st class honours from The University of Manchester in BSc Computer Science.
Whilst working full time, I studied at Birkbeck, University of London, gaining an MSc Advanced Information Systems.
In 2010, during my MSc studies, I was introduced to machine learning and neural networks. Machine learning has since taken the world by storm and I've been happy to use this skillset in projects for my clients!
Technical Skills
I am a multilingual programmer and have previously worked in a number of languages including Java, PHP, and Perl. In recent years, full-stack JavaScript has been my preference, using Node.js on the backend and typically Vue.js or React on the frontend.