PYTHON

IWrite a linear regression function using no public libraries to do a multivriate regression.

Write a function named linear_regression to implement Linear Regression without using public libraries related to regression. The inputs of this function should be predictor values (X or X_1), a target value (Y), a learning rate (lr), and the number of iterations (repetition). The function must build a linear model using gradient descent and output the model (params) and loss values per iteration (loss). Set the iteration to 10000 and calculate and show the mean squared error (MSE) for the models obtained from both X and X_1 predictors (hint: you might write another function named predict to predict the values based on X or X_1 and params) and plot the learning curve (loss) for both models in one figure (hint: use log scaling plot). Try different learning rates and show the results.