Python for Machine Learning - The Complete Beginners Course - Line Representation

The video tutorial explains the linear equation Y = mX + b, where Y is the dependent variable and X is the independent variable. It describes the slope (m) and Y-intercept (b) and applies this equation to real estate, using surface area as the independent variable to predict house prices. The tutorial also covers finding the best fit values for m and b to make accurate predictions.

What new insight or understanding did you gain from this video?