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Large scale non-linear learning on a single CPU


This talk presents several methods for learning non-linear models on a single machine, where the dataset does not fit into ram. It will cover the hashing trick, kernel approximations, neural networks, and extreme learning machines (random neural networks). This will be a fairly technical talk, showing off some of the lesser known out-of-core capabilities of scikit-learn.


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