My implementation of a linear regression model. A rough implementation that uses a constant learning rate and number of epochs. Currently working on using grid search to optimize these parameters.
This implementation applies the gradient descent algorithm in order to reduce error and optimize the coefficients. The loss function is based on the mean-squared error function (sum(errors)^2 / n).