Gradient Descent Explained Fast & Simple Machine Learning!
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Gradient Descent Explained Fast & Simple Machine Learning!
Gradient Descent (GD) is the mathematical optimization problem solver that allows machines to learn how to generate new faces, play hide-and-seek, and beat humans at games like Dota. GD is the process used to find the right value of data (θ) that makes the overall cost function as small as possible. For simple and fast execution, Stochastic ...
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Insightforge | Data Science & AI on Instagram: "Gradient Descent is an optimization technique used to train machine learning models — it helps find the best set of parameters (like weights in a neural network) that minimize the loss function. Imagine the loss function as a hilly surface every point represents a different combination of parameters. Our goal? To move downhill toward the lowest point (minimum loss). To know which way to move, we calculate the gradient, which shows how the loss chan
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