Convergence Algorithm, Machine Learning, Gradient Descent, Global Minima, Multiple Linearregression.
Since my d J(θj) /d(θj) is a negative value θj := θj - α (negative value)) θj := θj + positive value * Here this means we have add a positive value to the current θj to get the Global Minima If I get a slope as a positive value, θj := θj - α (d J(θj) /d(θj)) Since my d J(θj) /d(θj) is a positive