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.

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