why is h(x)=(theta0+theta1(x))**2?
why it is squared?
Error function in gradient descent
h(X) is always defined as theta(transpose) of X. There’s no square term involved in it. There must be a confusion from side. In the video always, the term theta0 + theta1*X1 is represented as h(X). The square is present when we are defining the loss function and that too, (h(X) - Y)**2.
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