This project analyzes user logging data to identify potential anomalies using machine learning methods and comparing their performance.
Languages, packages, and software used:
- Python (pandas, scikit-learn, oracledb, numpy, xgboost, datetime, scipy.stats)
- SQL (Oracle Database)
Repository structure:
-
src/ - source code
- loading_data.py - data loading from an Oracle database and CSV files
- main.py - ML model implementation
- preprocessing.py - data preprocessing
-
README.md