Instruction: Explain the concept of gradient descent and its role in optimizing machine learning models.
Context: This question assesses the candidate's understanding of a fundamental optimization algorithm in machine learning.
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The way I'd explain it in an interview is this: Gradient descent is the process of improving a model step by step by adjusting its parameters in the direction that reduces the loss. At each iteration, you calculate how the loss changes with respect to the parameters, then move...