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5. Consider the problem of predicting how well a student does in her second year of college/university, given how well she did in her first year. Specifically, let x be equal to the number of "A" grades (including A-. A and A+ grades) that a student receives in their first year of college (freshmen year). We would like to predict the value of y, which we define as the number of "A" grades they get in their second year (sophomore year). Here each row is one training example. Recall that in linear regression, our hypothesis is he(x)=0o+O;x, and we use m to denote the number of training examples. y 4 3 4 1 4 3 For the training set given above, what is the value of m? (which should be a number between 0 and 10).

5. Consider the problem of predicting how well a student does in her second year of college/university, given how well she did in her first year. Specifically, let x be equal to the number of "A" grades (including A-. A and A+ grades) that a student receives in their first year of college (freshmen year). We would like to predict the value of y, which we define as the number of "A" grades they get in their second year (sophomore year). Here each row is one training example. Recall that in linear regression, our hypothesis is he(x)=0o+O;x, and we use m to denote the number of training examples. y 4 3 4 1 4 3 For the training set given above, what is the value of m? (which should be a number between 0 and 10).

Computer Networking: A Top-Down Approach (7th Edition)
Computer Networking: A Top-Down Approach (7th Edition)
7th Edition
ISBN:9780133594140
Author:James Kurose, Keith Ross
Publisher:James Kurose, Keith Ross
Chapter1: Computer Networks And The Internet
Section: Chapter Questions
Problem R1RQ: What is the difference between a host and an end system? List several different types of end...
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5. Consider the problem of predicting how well a student does in her second year of college/university, given how well she did in her first year. Specifically, let x be equal to the number of "A" grades (including A-. A and A+ grades) that a student receives in their first year of college (freshmen year). We would like to predict the value of y, which we define as the number of "A" grades they get in their second year (sophomore year). Here each row is one training example. Recall that in linear regression, our hypothesis is he(x)=0o+O;x, and we use m to denote the number of training examples. y 4 3 4 1 4 3 For the training set given above, what is the value of m? (which should be a number between 0 and 10).
Transcribed Image Text:5. Consider the problem of predicting how well a student does in her second year of college/university, given how well she did in her first year. Specifically, let x be equal to the number of "A" grades (including A-. A and A+ grades) that a student receives in their first year of college (freshmen year). We would like to predict the value of y, which we define as the number of "A" grades they get in their second year (sophomore year). Here each row is one training example. Recall that in linear regression, our hypothesis is he(x)=0o+O;x, and we use m to denote the number of training examples. y 4 3 4 1 4 3 For the training set given above, what is the value of m? (which should be a number between 0 and 10).
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