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Solution: Convex Optimization

Explore how to solve convex optimization problems by implementing maximum likelihood estimation for the beta distribution. Learn to compute optimal parameters using gradient equations and verify results with NumPy sampling.

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Explanation

The probability density function of the beta distribution with the shape parameter θ\theta is given as follows:

for x[0,1]x \in [0,1] ...