Can you explain what gradient descent is?
Sure! Gradient descent is an optimization algorithm used to minimize a function by iteratively moving towards the steepest descent.
How does it work in machine learning?
In machine learning, gradient descent helps to minimize the loss function, allowing the model to learn from the data.
What are the different types of gradient descent?
There are several types, including batch gradient descent, stochastic gradient descent, and mini-batch gradient descent.
What are the advantages of using gradient descent?
Gradient descent is efficient for large datasets and can converge to a local minimum quickly, making it widely used.
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