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 does the equation Y = m * X + b represent?

Explain the roles of Y, X, M, and B in the equation.

What is the significance of the slope (M) in a linear equation?

How is the price determined based on surface area in the context of the equation?

What process will be used to find the best fitted values for M and B?