This folder contains the necessary files of Project 1 for the course CS-433.

• implementations.py : This file implements the basic functions required in Step 2, along with additional functions essential for their operation. The asked ones are
  - mean_squared_error_gd
  - mean_squared_error_sgd
  - least squares
  - ridge regression
  - logistic regression
  - reg logistic regression

• run.py : The script contained in this file reproduces exactly the .csv predictions (see final_results folder) generated with our ML methods.

• Project_1_Report.pdf : In this this report, the main problem is first briefly explained. Then, the methodology is developped and the results are illustrated

• final_results : This folder contains one .csv file, which represents the prediction obtained thanks to our model. The individuals are denoted by "Id" and the predictions are labeled by {-1,+1} depending if a potential heart attack is predicted or not, respectively.