In this video, I have explained about Gradient Descent Optimizer and Back Propagation Algorithm mathematically. Also explained the weight updation formula for Gradient Descent Optimizer and Loss Calculation.
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Gradient descent is the most commonly used optimization technique in deep learning and machine learning. It calculates the first derivative when we want to perform updates on weights -the ultimate goal is to reach global minima.
Gradient descent is an optimization algorithm that's used when training a machine learning model. It's based on a convex function and tweaks its parameters iteratively to minimize a given function to its local minimum.
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