February 23-25, 2022
Montreal, Canada

Deep Learning for the Web using TensorFlow.js

This course will teach you how to use Machine Learning in JavaScript applications and websites. Deep Learning and Neural Networks have seen a lot of success in recent years, but they still seem intimidating to many. Our goal is to make it as simple as possible without having to have a math degree to participate.

Get hands-on experience with deep learning using JavaScript and expand your knowledge of building, training, and running machine learning models in the browser using the latest version of TensorFlow.js.

What you will learn:

  • Introduction to Deep Learning and Neural Networks
  • Introduction to TensorFlow.js
  • Tensors: uses and types
  • Models: saving and loading a model
  • UI: creating the UI; visualizing predictions
  • Classifiers: binary and multi-class
  • Adding a toxicity model classifier to a chat app for moderation
  • Preparing the data, designing, training, and testing models
  • Extending pre-trained models
  • Working with images: convolutions and image classification
  • Adding automatic image captioning to a web app using MobileNet
  • Deployment and performance: bundle optimizations
  • Bonus: Natural Language Processing and AI Assistants

Who is the target audience?
Anyone who wants to integrate machine learning into their apps or websites using JavaScript. No previous experience with machine learning is necessary.

You should be comfortable with JavaScript and have at least basic knowledge of HTML and CSS.

Gerard Sans

Google Developer Expert; former AWS Amplify team

Gerard loves helping Developers to succeed using Web and Cloud technologies. He is very excited about the future of the Web and JavaScript. Always happy Computer Science Engineer and humble Angular GDE. He loves to share his learnings by giving talks, training and writing about cool technologies. He loves running GraphQL London, GraphQL San Francisco, mentoring students and giving back to the community.

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