GD algorithm Consider Linear Regression with single variable (univariate) problem. What will be the (approximate if can’t say accurately) values of derivatives of cost/loss function ‘J’ w.r.t. all the parameters by considering one at a time, and why? What is the significance and/or usage of these θj* for the cost function ‘J’ and hypothesis ‘h’? Given a dataset where first column is the label ‘y’ while other columns represent factors ‘xi’ as follows: X = [       1            0            1 0            1            0 ] Using GD algorithm, find the linear model. Show all the calculations

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  1. GD algorithm
    1. Consider Linear Regression with single variable (univariate) problem.
      1. What will be the (approximate if can’t say accurately) values of derivatives of cost/loss function ‘J’ w.r.t. all the parameters by considering one at a time, and why?
      2. What is the significance and/or usage of these θj* for the cost function ‘J’ and hypothesis ‘h’?
    2. Given a dataset where first column is the label ‘y’ while other columns represent factors ‘xi’ as follows:

X = [       1            0            1

0            1            0 ]

Using GD algorithm, find the linear model. Show all the calculations

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