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What is gradient descent and how does it work?
Gradient descent is an optimization algorithm used to minimize a function by iteratively moving in the direction of steepest descent. pg. 47

The algorithm works by computing the gradient of the loss function, then updating parameters in the opposite direction scaled by the learning rate. pg. 48
Give me 3 quiz questions on this topic
Quiz generated! ✨
Q1: What does gradient descent minimize?
Q2: Why do we move opposite to the gradient?
Q3: What is the role of learning rate?

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