I think the algorithm fails if we guess w , b at local maxima

[image] Gradient Descent starting at the "top of the hill" Week 1 Supervised ML: Regression and Classifica... Always exciting to revisit these fundamental concepts as we look at things differently. I was curious about the starting point for Gradient Descent when you are o…

For most simple regression systems, the cost function is known to be convex. So a local maximum is not possible.

May I encounter cost function in other models that may cause the gradient descent algo to converge to a local maxima? How to prevent it in that case? Thx.

If any of the initial weight values cause the gradients to be non-zero, you won’t start at a maximum, and the gradients will lead away from the maximum on the first iteration. You would have to be extremely unlucky to choose initial weight values that had all of the gradients at exactly zero. In p…

What if we get local maxima when we choose w, b in gradient descent algorithm

Course Q&A Machine Learning Specialization Supervised ML: Regression and Classification

tharunnayak14 July 7, 2022, 12:57pm 2

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What if we get local maxima when we choose w, b in gradient descent algorithm

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