2D Linear Regression Using Gradient Descent Implementation

In this notebook, we will walk through how to perform linear regression using gradient descent. The goal for this example is to predict what the profit for a new food truck might be given the population of the city. The input data to our model will be the population of a city, and the output data of our model will be the predicted profit. Since this is a 2-D linear regression model, the classic equation of the line (y = m * x + b) will be our model.