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Linear Regression using Gradient Descent
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Please help me solve this problem. Major in computer science. Class: Machine LearningExercise 1 (7 points)1a. Explain the idea of the gradient descent algorithm, define the cost function, and the rule of updating the coefficient of linear regression.1b. Explain why the cost function of logistic regression can be estimated by the following formulation:E0 = -[ylog(hx) (1-y)log(1-hx)]1c. Assuming at a certain iteration of batch-gradient descent, we reach the global maximum value of the cost funct
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