Linear regression equation

In algebraic terms, the model would be defined as:

Where:

• y is miles per gallon—the value we want to predict.
• m is the slope of the line.
• x is pounds—our input value.
• b is the y-intercept of the line.

In ML, we write the equation for a linear regression model as follows:

Where:

• y' is the predicted label—the output.
• b Bias is a parameter of the model and is calculated during training.
• $w_1$ Weight is a parameter of the model and is calculated during training.
• $x_1$ is a feature—the input.