Enron was one of the largest companies in the US, however, it bankrupted in 2002. The goal of this project is to identify persons of interest, who were believed to be responsible for company fraud, based on the dataset given. In this process, I will make some data cleaning and extract key features, and then use machine learning to train the features. Finally I will test the model to see its performance.

poi_id.py is the final python code used to implement data cleaning, machine learning and test performance.

poi_id_complex includes all codes that I have used. It is way too complex.

The final_project_dataset.pkl is the original dataset.

The three other pkl datasets, my_classifier.pkl, my_dataset.pkl,my_feature_list.pkl, are generated automatically by poi_id.py, which will be used to test performance.

There is a report describing the entire procedure and performance analysis.