Contains projects needed to complete Udacity's Data Analyst Nanodegree Program

Udacity Machine Learning

Machine learning algorithms applied to explore Enron email dataset and figure out patterns about people involved in the scandal.

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.

A quick Python implementation of a text generator based on a Markov process.

Machine Learning framework example for Business Email Classification.

This is the repository for my project, "Identifying Fraud from Enron Email ," for the Udacity Intro to Machine Learning Course

Working on Enron dataset.

A Spam Filter Python implementation without libraries using Naive Bayes Learning.

The Indexer crawls over the enron email dataset folders and indexed each file in the ZincSearch database. It also have a User Interface built with vue which allows you to search over the indexed files based on a keyword.

Machine Learning Basics

Use support vector machine to do text learning in order to classify email by authors

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..

A Person Of Interest Identifier Model, for the Enron Fraud Case, based on various Machine Learning Concepts.

Analysing Enron data.

Enron Network Centrality Analytics. First Assignment for Data Analytics course @unimib18/19.

This Repo holds the projects, which I completed as part Udacity Data Analyst Nano Degree. 👨‍🎓🤘

Anomaly Detection on the Enron financial-email dataset, using specialised unsupervised machine learning algorithms: One-class SVM, Isolation Forest, LOF.