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A key strength of neural networks is their composability which allows them to process different forms of input and output data. In this talk, Matt describes the basic building blocks of neural networks and how they handle varying types of data (such as images & text) as well as varying datasets sizes. He reviews how a novel set of problems can be solved with interesting combinations of these pieces.
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