Consider the following data with one input (x) and one output (y):
Apply linear regression on this data, using the hypothesis $h_Θ(x) = Θ_0 + Θ_1 x$, where $Θ_0$ and $Θ_1$ represent the parameters to be learned. Considering the initial values $Θ_0$= 1.0, and $Θ_1$ = 0.0, and learning rate 0.1, what will be the values of $Θ_0$ and $Θ_1$ after the first three iterations of Gradient Descent
From least squares method I took the derivative with respect to $Θ_0$ and $Θ_1$ and plugged in the initial values to get the slope/intercept and multiplied it by the learning rate 0.1 to get the step size.The step size was used to calculate the new $Θ_0$ and $Θ_1$ values.
I am getting $Θ_0$ as 1.7821 when following the above. Please let me know if the approach followed and the solution correct or there is a better way to solve