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What is L23 Stochastic Gradient and Mini Batch about?

This lecture discusses stochastic optimization methods for maximizing an objective function. It covers stochastic gradient ascent, where the gradient is estimated using a single random data point, and mini-batch stochastic gradient ascent, which uses a random batch of data. Logistic regression is provided as an example application of these methods. Code is presented to implement stochastic gradient ascent for logistic regression to estimate model parameters.

Author

Ananya Agarwal

Language

EN