What is gradient descent in deep learning?
An example of an AI chatbot conversation about gradient descent in deep learning.
What is gradient descent in deep learning?
Gradient descent is an optimization algorithm used to minimize the loss function in deep learning models.
How does gradient descent work?
It works by iteratively adjusting the model parameters in the direction of the steepest descent of the loss function.
What are the different types of gradient descent?
The main types are batch gradient descent, stochastic gradient descent, and mini-batch gradient descent.
Why is gradient descent important?
It's crucial for training models effectively, as it helps find the optimal parameters that minimize errors.
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