# Linear regression

Housing prices (size in feet => price in USD)

- m - number of examples in the dataset
- X's - input variables, features
- y's - output variables, target variables
- (X, y) - single training example
- (Xi, yi) - i-th training example

- Training set => Learning Algorithm => h (hypothesis)
- is function that converts X to estimated y. y = h(X) as it is a linear function we can also write h(x) = ax^2 + b (a, b could be theta 0 and 1)

- Linear regression with one variable (aka.) Univariate Linear regression.