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Exercise: Using Gradient Descent to Minimize a Cost Function

Explore the gradient descent process to minimize a cost function by analyzing parameter updates and step sizes. Learn to implement iterative steps, adjust learning rates, and understand convergence toward optimal solutions in logistic regression models.

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Approach to minimize the cost function

In this exercise, our task is to find the best set of parameters in order to minimize the following hypothetical cost function: y=f(x)=x2–2xy = f(x) = x^2 – 2x ...