# Machine Learning Course Dependencies
# Python 3.8+ required

# Core Libraries
numpy>=1.21.0
pandas>=1.3.0
scikit-learn>=1.0.0
scipy>=1.7.0

# Visualization
matplotlib>=3.4.0
seaborn>=0.11.0
plotly>=5.3.0

# Deep Learning
tensorflow>=2.7.0
torch>=1.10.0
keras>=2.7.0

# Gradient Boosting
xgboost>=1.5.0
lightgbm>=3.3.0
catboost>=1.0.0

# Utilities
jupyter>=1.0.0
jupyterlab>=3.2.0
ipython>=7.30.0
notebook>=6.4.0

# Data Processing
openpyxl>=3.0.9
xlrd>=2.0.1
statsmodels>=0.13.0

# Model Evaluation
mlxtend>=0.19.0
imbalanced-learn>=0.8.0
shap>=0.40.0

# Web Framework (for interactive demos)
streamlit>=1.15.0
dash>=2.7.0

# Documentation
sphinx>=4.3.0
nbsphinx>=0.8.0