Learn TensorFlow.js - Deep Learning and Neural Networks with JavaScript

Overview

This course teaches how to deploy and run deep learning models in the browser using TensorFlow.js. By the end of the course, learners will be able to build and deploy a web application that runs a neural network to classify images. The course covers topics such as client-server deep learning architectures, converting Keras models to TFJS models, serving models with Node.js, tensor operations, and more. The teaching method includes video tutorials and practical hands-on coding exercises. This course is intended for individuals interested in deep learning, neural networks, and web development, with a focus on using JavaScript for machine learning applications.

Syllabus

- Intro to deep learning with client-side neural networks.
- Convert Keras model to Layers API format.
- Serve deep learning models with Node.js and Express.
- Building UI for neural network web app.
- Loading model into a neural network web app.
- Explore tensor operations with VGG16 preprocessing.
- Examining tensors with the debugger.
- Broadcasting with tensors.
- Running MobileNet in the browser.