solve step by stepif you need to use software, you have to use python. Q1. The table

solve step by stepif you need to use software, you have to use python.

 

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Q1. The table below gives the number of hours spent studying for an ML exam (x), and the final exam grade (y). x 2 5 1 0 4 2 3 y 77 92 70 63 90 75 84 Find the linear regression model that fits the data and the predicted grade for a student who studied for 6 hours? Q2. The table below represents the relation between prices of houses (y) and their sizes (x_1) in meter square and number of rooms (x_2). X 1 40 50 50 60 100 X 2 1 2 1 2 4 y 100 110 80 120 160 a. Walk through the steps of finding a linear regression model that fits the data in a closed form expression. Define the objective function and the way you solve it to yields the final closed form solution. b. Compute the predicted price of a house of size 80m and has 3 bedrooms? c. Find the updated value of the model after performing each GD iteration for total of 3 iterations if the learning rate a = 0.001, and = [1,0.5,0]. Q3. Suppose you trained a logistic regression classifier, and your hypothesis is: fg = g(o +1x1 + Bx2) Plot the decision boundary of this classifier when: a. Bo 5. =0, = -1. b. Bo = -4,B=1=1. c. Bo 4,B =1 = 1. Q4. The table below represents the relation between the type of tumor (y), where y=0 means benign and y=1 means malignant and its size in cm (x 1) and age in months (x_2). X_1 10 X_2 1 0 230 40 40 60 2 1 4 1 0 1 y Walk through the steps of finding a logistic regression model that fits the data. Define the objective function then find the updated value of the model after performing each GD iteration for a total of 3 iterations. Assuming = [1, 0.5,0], a = 0.001. Q1. The table below gives the number of hours spent studying for an ML exam (x), and the final exam grade (y). x 2 5 1 0 4 2 3 y 77 92 70 63 90 75 84 Find the linear regression model that fits the data and the predicted grade for a student who studied for 6 hours? Q2. The table below represents the relation between prices of houses (y) and their sizes (x_1) in meter square and number of rooms (x_2). X 1 40 50 50 60 100 X 2 1 2 1 2 4 y 100 110 80 120 160 a. Walk through the steps of finding a linear regression model that fits the data in a closed form expression. Define the objective function and the way you solve it to yields the final closed form solution. b. Compute the predicted price of a house of size 80m and has 3 bedrooms? c. Find the updated value of the model after performing each GD iteration for total of 3 iterations if the learning rate a = 0.001, and = [1,0.5,0]. Q3. Suppose you trained a logistic regression classifier, and your hypothesis is: fg = g(o +1x1 + Bx2) Plot the decision boundary of this classifier when: a. Bo 5. =0, = -1. b. Bo = -4,B=1=1. c. Bo 4,B =1 = 1. Q4. The table below represents the relation between the type of tumor (y), where y=0 means benign and y=1 means malignant and its size in cm (x 1) and age in months (x_2). X_1 10 X_2 1 0 230 40 40 60 2 1 4 1 0 1 y Walk through the steps of finding a logistic regression model that fits the data. Define the objective function then find the updated value of the model after performing each GD iteration for a total of 3 iterations. Assuming = [1, 0.5,0], a = 0.001.