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Build your own "Not Hotdog" deep learning model

Description

This talk focuses on the code and concepts behind image classification models. First, I'll break down how convolutional neural networks work. I'll present a few methods for dealing with small amounts of training data (data pre-processing and image augmentation / transformations). I'll show how to leverage (and extend) a network that's been pre-trained on a large image dataset (transfer learning). I'll use libraries like Keras and Tensorflow, and I'll show a working prototype (and open-source it) that identifies photos of pizza, because pizza (NY style of course) is way better than hotdogs :)

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