A Person Of Interest Identifier Model, for the Enron Fraud Case, based on various Machine Learning Concepts.
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Updated
Nov 9, 2017 - Python
A Person Of Interest Identifier Model, for the Enron Fraud Case, based on various Machine Learning Concepts.
🤖 Codes and notes from Udacity Intro to Machine Learning course.
This is the repository for my project, "Identifying Fraud from Enron Email ," for the Udacity Intro to Machine Learning Course
This Repo holds the projects, which I completed as part Udacity Data Analyst Nano Degree. 👨🎓🤘
A Person Of Interest (POI) identifier in the Enron Email and Financial Dataset; as the project for Intro to Machine Learning in Python for the Data Analyst Nanodegree, Udacity..
Machine learning algorithms applied to explore Enron email dataset and figure out patterns about people involved in the scandal.
Use support vector machine to do text learning
Udacity Machine Learning
Enron Network Centrality Analytics. First Assignment for Data Analytics course @unimib18/19.
Contains projects needed to complete Udacity's Data Analyst Nanodegree Program
Email Datasets can be found here
A Spam Filter Python implementation without libraries using Naive Bayes Learning.
A Person Of Interest identifier based on ENRON CORPUS data.
A quick Python implementation of a text generator based on a Markov process.
Machine Learning framework example for Business Email Classification.
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.
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