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Write a Python program that implements gradient descent for minimizing
the least squares loss. As a stopping condition check for the objective
between the current and previous iteration. If the objective improves
by less than theta then you stop. The input and output should be the same
as for nearest means and Naive-Bayes.
Test your program with the input data
0 0
0 1
1 0
1 1
10 10
10 11
11 10
11 11
Write a Python program that implements gradient descent for minimizing
the least squares loss. As a stopping condition check for the objective
between the current and previous iteration. If the objective improves
by less than theta then you stop. The input and output should be the same
as for nearest means and Naive-Bayes.
Test your program with the input data
0 0
0 1
1 0
1 1
10 10
10 11
11 10
11 11
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