Issue #78
Gradient Descent in ML
Business Analytics Newsletter
· 2 min read
Hi !
Welcome to the new edition of Business Analytics Review !
Today, we're diving into the heart of many machine learning algorithms: gradient descent.
Imagine you're hiking up a mountain. You're not just randomly wandering; you're constantly checking the slope and adjusting your path to find the easiest, most efficient way to reach the summit. Gradient descent works similarly. It's an optimization algorithm that iteratively adjusts the parameters of a model to minimize a cost function.
Think of the cost function as the "height" of the mountain. Gradient descent calculates the slope (gradient) at the current position and takes a step in the direction that leads to the steepest descent. By repeatedly taking small steps, the algorithm gradually moves towards the lowest point on the "mountain," which represents the optimal solution.
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