ML tutorial: How to solve classification problems with TensorFlow and multi-layer perceptrons

From the creator

Up until now you learnt about how to solve regression problems. In this video you will switch hats to solve classification problems - that is what class something belongs to. Learn how to handle data with thousands of inputs such as images, where each pixel is a feature, and instead of regression to predict a number you will solve a classification problem to predict what class an image belongs to. This video covers what classification is and how to create an image classifier for the MNIST dataset that can classify handwritten digits that works via TensorFlow.js right in the web browser introducing new concepts such as 1-hot encodings to represent your class data and categorical cross entropy. 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 ↗
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