Gradient Descent in Machine Learning: Python Examples
Gradient Descent in Machine Learning: Python Examples
Apr 22, 2024
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AI • Machine Learning • Tech on Instagram: "Gradient descent is an important AI algorithm that helps machine learning models learn by improving themselves over time. Imagine you’re trying to find the lowest point in a landscape with hills while blindfolded—you’d take small steps in the direction that feels downhill. Similarly, gradient descent adjusts a model’s internal parameters (weights and biases in a neural network) by calculating the direction and size of the “step” needed to reduce error—
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AI | Machine Learning | Tech on Instagram: "Follow for more @ai.pathwayy Gradient descent is an optimization method used to train machine learning models by finding the set of parameters (like weights in a neural network) that make the loss function as small as possible. You can think of the loss as a surface, where each point represents a different set of parameters, and our goal is to move downhill toward the lowest point. To do this, we calculate the gradient, which is a collection of partial
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