Dive into client-side artificial neural networks with this comprehensive video tutorial on TensorFlow.js. Build and deploy a web application that runs a neural network in the browser to classify images. Explore client-server deep learning architectures, convert Keras models to TFJS models, serve models with Node.js, and master tensor operations. Cover topics such as introducing deep learning with client-side neural networks, converting Keras models to Layers API format, serving deep learning models with Node.js and Express, building UI for neural network web apps, loading models into web applications, exploring tensor operations with VGG16 preprocessing, examining tensors with the debugger, broadcasting with tensors, and running MobileNet in the browser. By the end of this 1-2 hour course, gain practical experience in implementing deep learning applications directly in web browsers using TensorFlow's JavaScript library.
Overview
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.
Taught by
freeCodeCamp.org
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