What Is Gradient Descent? | Built In
What Is Gradient Descent? | Built In
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Gradient Descent in Machine Learning: Python Examples
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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: "Gradient descent is an iterative optimization technique 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. Given a simple surface, we calculate the gradient, which is the collection of partial derivatives of the loss with respect to x and y. A partial derivative tells us how the loss changes if we tweak just one parameter while holding the others co
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