requirements.txt

# Core libraries for data manipulation and numerical computation
pandas==2.2.2   # High-performance data manipulation and analysis library
numpy==1.26.4   # Library for numerical computations and array operations

# Visualization libraries for creating plots and charts
matplotlib==3.8.0   # Comprehensive library for static, animated, and interactive visualizations
seaborn==0.13.2     # Statistical data visualization library built on top of matplotlib

# Machine learning library for data preprocessing, model training, and evaluation
scikit-learn==1.5.2   # Widely used machine learning library with tools for predictive modeling

# Gradient boosting algorithm for regression and classification
xgboost==2.1.2   # Optimized distributed gradient boosting library

# Automated machine learning tool for creating ML pipelines
tpot==0.12.2   # Automated machine learning library for pipeline optimization