Advanced machine learning for web developers: Autoencoders, GANs, RNNs and more

From the creator

Congratulations on completing Google's Machine Learning for Web Developers and creatives course. From learning the basics of machine learning to creating a full end-to-end web app that can detect spam using a natural language model. You completed an in-depth introduction to Machine Learning with a JavaScript specific lens using TensorFlow.js to use Web ML right in the browser. This video wraps up your learnings with a review of the course outline, new model architectures to explore that build upon your current knowledge, and further resources worth checking out. Remember to ask questions on the forum to discuss or share ideas with your peers: https://discuss.tensorflow.org/tag/tfjs - ensure you tag with TFJS so we can find it! Finally for a chance to be featured at future events remember to use the hashtag WebML for any creations you make - we would love to see what you make with Machine Learning in JS! Resources: Codelabs →https://goo.gle/3RVWwhK Github →https://goo.gle/3xaVLaP Website / API → https://goo.gle/3jLoGzc Models → https://goo.gle/3Yj4GTy Github Code → https://goo.gle/3DZgCBP Forum → https://goo.gle/3IbMcyS Codepen→ https://goo.gle/3Xn0nFE Glitch →https://goo.gle/3YCHRdi Catch more episodes from Machine Learning for Web Developers (Web ML) → https://goo.gle/learn-WebML Check out TensorFlow on YouTube → https://goo.gle/TensorFlow-YouTube Subscribe to Google Developers → https://goo.gle/developers Connect with Jason Mayes to ask questions: LinkedIn → https://goo

Published 2023-02-11 · Watch on YouTube ↗
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