📧 A data engineering exercise
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Updated
Feb 4, 2017 - Python
📧 A data engineering exercise
The fraud identification models were build using Python Scikit-learn machine-learning module.
Predict whether an individual is a person of interest based on their enron email.
Enron Email Analysis
Machine learning algorithms are used to determine some possible people involved in Enron fraud---Udacity project
Identifying and cleaning the outliers of the Enron Dataset.
Email Datasets can be found here
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.
A project on Extract-Transform-Load (ETL) operations performed on the emails from the infamous enron corpus database.
The code and data for "Are Large Pre-Trained Language Models Leaking Your Personal Information?" (Findings of EMNLP '22)
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