Convergence Algorithm, Machine Learning, Gradient Descent, Global Minima, Multiple Linearregression.
have to find it for j = 0 and j = 1 if j = 0 ; d J(θ0,θ1) /d(θ0) = d 1/2m [i =1 -> m Σ (hθ(x)^i - y^i)^2] /d(θ0) // Since hθ(x)=θ0+θ1x and θ1x is a constant d hθ(x)/ dθ0 = 1 J(θ0,θ1) /d(θ0) = 1/m [i =1 -> m Σ (hθ(x)^i - y^i)] * 1 if j = 1; d J(θ0,θ1) /d(θ1) = d 1/2m [i =1 -> m Σ (hθ(x)^i - y^i)^2]