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John Myles White surveys some basic methods for analyzing data in a streaming manner with a focus on using stochastic gradient descent (SGD) to fit models to data sets that arrive in small chunks. Some basic implementation issues are shown, demonstrating the effectiveness of SGD for problems like linear and logistic regression as well as matrix factorization.
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