This video shows a step-by-step implementation of logistic regression class in python. A detailed implementation of batch gradient ascent for log likelihood maximization is explained and applied to train classifiers for handwritten digits classification. Using a one-vs-all (one-vs-rest) scheme the binary classification problem is expanded to a multiclass classification problem.
** The python code for this video can be found on Github:
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