Problem 3.7d
The problem asks us to prove that the optimal column vector is in the opposite direction of the inverse of the Hessian times the gradient.
But didn't the chapter prove that the optimal column vector is in the opposite direction of the gradient? 
Re: Problem 3.7d
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Hope this helps. :) 
Re: Problem 3.7d
Could you possibly redescribe the Problem 3.17b for me? I don't quite understand the requirements of this question. What's the relation between it and the gradient descent algorithm for logistic regression of the textbook?
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