Gradient descent for classification problems
Gradient Descent is an iterative optimization algorithm used to minimize the cost function or error in machine learning models. It is a fundamental algorithm in the training of models, particularly in the context of supervised learning. In this video we discuss how the algorithm applies to binary classification and in particular, how the cost function should be chosen.
Coding assignments: https://github.com/ionpetre/FoundML_c...
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