Linear Regression

Situation

I have some data, and would like to build a model using this training data to predict the y values of future x values.

Procedure

• Model

$$f_{w,b}(x^{(i)}) = wx^{(i)} + b $$

• Parameters

w,b

• cost function

$$J(w,b) = \frac{1}{2m} \sum\limits_{i = 0}^{m-1} (f_{w,b}(x^{(i)}) - y^{(i)})^2 $$

• goal:

minimize J(w,b)

Gradient descent

I used Gradient descent to minimize my cost function.