4.5.2: Multi-layer perceptrons - Deep neural networks for non linear data

From the creator

In this video you will go beyond the single perceptron (neuron) and combine multiple such that they can find patterns in more complex input training data that may be non linear. Learn about layers of neurons and how they can be combined into multi layer perceptrons or deep neural networks along with the tradeoffs of doing so. Learn through actual exercises to find the sweet spot that provides a good balance between minimizing loss and computational complexity of the network to give you the best results. 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.gle/3GwgeLw Twitter →https://goo.gle/3Xh6MT7 Discord →https://goo.gle/3WWVO5t Use #WebML to share your learnings and creations from this course to meet your peers on social media! See what others have already made with Web ML → http://goo.gle/made-with-tfjs

Published 2023-02-06 · Watch on YouTube ↗
Availability and playback restrictions are controlled by the original channel.