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Finding needles in haystacks with Deep Neural Networks


PyData London 2016

With an inventory of millions of products, finding duplicates is intractable by hand. Neural networks can be used to learn a representation that maps duplicates close together in a manifold.

We trained a network to perform multi-task classification. Using this as a basis, we trained a manifold that maps images to a space where duplicates have a small distance and different products have a large distance.

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