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Gradient descent: Difference between revisions
Created page with "{{see also|Machine learning terms}} ===Introduction== Gradient descent is a popular optimization algorithm in machine learning. It works by finding the minimum cost function, which can be adjusted to minimize errors between predicted output and actual output from a model. Gradient descent utilizes weights and biases as input parameters to achieve this minimal error margin. ==How Gradient Descent Works== Gradient descent works by iteratively altering the parameters of a..."
(Created page with "{{see also|Machine learning terms}} ===Introduction== Gradient descent is a popular optimization algorithm in machine learning. It works by finding the minimum cost function, which can be adjusted to minimize errors between predicted output and actual output from a model. Gradient descent utilizes weights and biases as input parameters to achieve this minimal error margin. ==How Gradient Descent Works== Gradient descent works by iteratively altering the parameters of a...") |
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