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Project : Identify Fraud From Enron Email

Project work done as part of Udacity's Data Analyst Nanodegree course.

The Enron Corpus is a large database of over 600,000 emails generated by 158 employees of the Enron Corporation and acquired by the Federal Energy Regulatory Commission during its investigation after the company's collapse.

Enron Email Dataset downloaded from : https://www.cs.cmu.edu/~enron/.
And it is the May 7, 2015 Version of dataset.

Getting started:

Clone this Udacity git repository
Running the startup.py file present in this repository will automatically download the tarred and gzipped dataset and extract it for usage.

Project Overview

In 2000, Enron was one of the largest companies in the United States. By 2002, it had collapsed into bankruptcy due to widespread corporate fraud. In the resulting Federal investigation, there was a significant amount of typically confidential information entered into public record, including tens of thousands of emails and detailed financial data for top executives. In this project, use the machine learning skills learnt in the Udacity course, to building a person of interest identifier based on financial and email data made public as a result of the Enron scandal.

  • poi_id.py file contains the basic python script for this project made by me to create the POI identifier.
  • three pickle files (my_dataset.pkl, my_classifier.pkl, my_feature_list.pkl) will be created after running the poi_id files and they aid the project reviewer.
  • tester.py - used by Udacity coaches along with the three pickle files to check the project submission.
  • /miniproject/ folder contains the miniprojects and assignments done during the Machine Learning course.
  • Project_report documents the steps and analysis done during the course of this project.

Python 2.7
scikit-learn 0.19.1