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Fundamentals of Machine Learning: A Pythonic Introduction

Gradient Descent

Explore the gradient descent algorithm to understand how it iteratively finds the minimum of a function by moving in the direction of steepest descent. Learn the importance of learning rate and initialization in ensuring effective convergence, and see how this method optimizes loss functions in machine learning models for better prediction accuracy.

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What is gradient descent?

Gradient descent is an optimization algorithm used for finding the minimum of a function. It’s an iterative algorithm that starts from an initial guess of the minimum and then takes steps in the direction of the negative gradientGradient is the vector of partial derivatives of a function concerning its variables, and it represents the direction and magnitude of the steepest ascent of the function. of the function at that point. The negative gradient of a function points in the direction of the steepest ...