Machine Learning, Data Science, Linear Regression, Gradient Descent, Numpy.
parameters θ = [m,q] in order to find the minimum of the cost function, this guarantees that on average the points of the dataset will not be too far from the line found. The Gradient Descent (GD) algorithm simply tells us that this update must follow the rule: θ = θ - α∇F(θ) Where α is an a priori