This repository contains Python scripts for analyzing network traffic data to classify IPs as compromised or non-compromised using a Support Vector Machine (SVM) model and to predict network traffic flows using a Random Forest Regressor model.
This was a project for a Machine Learning class during my Master's degree. The presentation is written in Portuguese and can be accessed here.
- Create a virtual env:
python -m venv venv- Load the virtual env:
source venv/bin/activate- Install all required packages:
pip install pandas numpy scikit-learn imbalanced-learn matplotlib seabornThis repository is using Gitflow Workflow and Conventional Commits, so if you want to contribute:
- create a branch from develop branch;
- make your contributions;
- open a Pull Request to develop branch;
- wait for discussion and future approval;
I thank you in advance for any contribution.
Finished