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requirements.txt

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+# Core numerical and IO
+numpy<2.0
+pandas==2.2.2
+joblib>=1.3
+
+# CPU ML fallback
+scikit-learn>=1.3
+
+# GPU array library (imported as `cupy` in the notebook)
+# Pick the CUDA 12.x wheel that matches your GPU drivers
+cupy-cuda12x>=12.0.0
+
+# Optional: used only for the simple GPU availability check in the notebook
+# (You can skip installing torch if you remove the torch check cell.)
+torch>=2.1
+
+# IMPORTANT: RAPIDS (cuDF, cuML) install instructions (NOT via pip)
+# The notebook uses RAPIDS cuDF/cuML for GPU RandomForest. Install via Conda:
+#
+#   conda create -n rapids-24.08 -c rapidsai -c conda-forge -c nvidia \
+#       rapids=24.08 python=3.10 cuda-version=12.2 -y
+#   conda activate rapids-24.08
+#
+# This will install `cudf` and `cuml` compatible with CUDA 12.2. If you're on Windows,
+# use WSL2 (Ubuntu) for best support. Native Windows support for RAPIDS is limited.
+
+# Windows-friendly GPU fallback (no RAPIDS required)
+# XGBoost supports GPU acceleration on native Windows when built with CUDA.
+# pip install xgboost will fetch a prebuilt wheel with GPU support if available.
+xgboost>=2.0
+
+# (Optional) Another alternative with some GPU support (requires separate setup):
+# lightgbm
+