# Core
numpy
pandas
scipy
scikit-learn
matplotlib
seaborn
joblib

# Gradient boosting / tree models
xgboost
lightgbm
catboost

# Regime detection
hmmlearn

# Feature selection / hyperparameter tuning / explainability
Boruta
optuna
scikit-optimize
shap

# Deep learning (neural ensemble)
torch

# Technical indicators
# NOTE: TA-Lib also needs the underlying C library installed on your system.
#   macOS:   brew install ta-lib
#   Ubuntu:  apt-get install ta-lib   (or build from source)
#   Windows: install a prebuilt wheel / the ta-lib binaries
TA-Lib

# Live data download (optional)
oandapyV20