This repository contains code for normalizing the Enron dataset.
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Updated
Aug 17, 2023 - Jupyter Notebook
This repository contains code for normalizing the Enron dataset.
Machine learning algorithms applied to explore Enron email dataset and figure out patterns about people involved in the scandal.
Identifying and cleaning the outliers of the Enron Dataset.
Phishing Detection classifier to filter fraudolent and phishing e-mail.
LT2212 V20 Assignment 3: Same-author-classification via feed-forward neural networks: Transformed email text (Enron) into a machine readable representation and built a classifier that determines whether two texts are authored by the same person or not.
Convolutional Neural Network to classify the emails of the enron data set
Learning how to use machine learning and deep learning algorithms/tips/tricks to solve practical problems in Python.
The final project for the University of Malta unit Web Intelligence (ICS2205). The 60% component involved an individual analysis on a twitter dataset using NetworkX. The 40% component involves half of group task where an analysis was performed on the enron email dataset using NetworkX.
Machine learning algorithms are used to determine some possible people involved in Enron fraud---Udacity project
Identify Fraud from Enron Email
Repository for the Final Project of the MIRI
Email Network Graph generator (Enron) - Utilizes Fusion Tables
Predict whether an individual is a person of interest based on their enron email.
[Incomplete] A chrome extension that tells you if a mail you're currently drafting is going to be classified as spam or not.
A project on Extract-Transform-Load (ETL) operations performed on the emails from the infamous enron corpus database.
Natural Language Processing (NLP) and programmatic data extraction in large scale fraud investigations.
Enron Email Analysis
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