Linear Regression, Gradient Descent, Machine Learning, Mathematics, Data Analysis.
θ0 as b, the y intercept, and θ1 as the slope, m. Thus, in univariate (dealing with one variable, x) linear regression, we must find a way to tweak these two thetas to get a line that best represents the line of best fit. Here, θ0 is the bias, in that it shifts the entire line by default (the y