Machine-Learning-Final-Project

Harvard AC209 final project. Please read written-report.pdf for project description and findings.

Authors

Andrew Sullivan.
James Liounis.
Kane Norman.

Repository Structure

The repository is organized as follows:

• notebook.ipynb: contains the trained machine learning models and scripts for training and tuning them (Former Name: Detecting_malicious_URLs.ipynb).
• detection_interface.py: contains the code for the web application that allows users to input a URL and receive a prediction from the model.
• Written_Report.pdf: documentation for the project, as well as a detailed analysis of our findings
• presentation_video_link.md: contains a YouTube link to our brief project presentation.

Dependencies

jupyter
matplotlib
numpy
pandas
pprint
pickle
scikit-learn
seaborn
tld
xgboost