Identification of Enron Employees who may have committed fraud based on the public Enron financial and email.
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Updated
Sep 23, 2018 - Python
Identification of Enron Employees who may have committed fraud based on the public Enron financial and email.
Enron Email ETL
Applied ML algorithms on Enron Dataset to predict Person of Interest (POI)
Identify Fraud from Enron Email and Financial datasets
Using Python, I explored and engineered data from Enron email metadata and financials, building and tuning a number of scikit-learn classification models to detect persons of interest.
Machine learning model for identifying persons-of-interest (POI) from Enron data
Machine Learning with Enron to identify person of interest. Implement different algorithms to discover what gives the best result
Natural Language Processing (NLP) and programmatic data extraction in large scale fraud investigations.
Phishing Detection classifier to filter fraudolent and phishing e-mail.
This is the repository for my project, "Identifying Fraud from Enron Email ," for the Udacity Intro to Machine Learning Course
Enron Email Search Tool. Fronted by React. Backed by Elasticsearch.
A Spam Filter Python implementation without libraries using Naive Bayes Learning.
Email Network Graph generator (Enron) - Utilizes Fusion Tables
Enron Network Centrality Analytics. First Assignment for Data Analytics course @unimib18/19.
📧 💰 Python + Machine Learning / I analyse the Enron Scandal data and try to predict those who were involved in the Enron fraud based on their financial data
This repository contains code for normalizing the Enron dataset.
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