kaggle images¶
Mirrors the Kaggle notebook environment. Package versions are pinned to match a Kaggle notebook pip freeze so code developed locally behaves identically when submitted to competitions. Three variants: NVIDIA GPU (with RAPIDS), CPU-only, and Apple Silicon.
kaggle-nvidia¶
Uses a custom PyTorch 2.10.0 wheel with Pascal support; Kaggle's own stock cu128 wheel has no Pascal kernels, so torch on Kaggle's P100s silently fails. Same version, but it actually works. Includes the RAPIDS stack as found in Kaggle GPU sessions.
RAPIDS hardware requirement
RAPIDS (cuDF/cuML/CuPy) requires Volta (sm_70) or newer. It is not functional on P100/GTX 10xx hardware; the same limitation applies on Kaggle itself.
| Component | Version |
|---|---|
| Base image | nvidia/cuda:12.8.1-cudnn-runtime-ubuntu24.04 |
| Python | 3.12 |
| CUDA | 12.8.1 |
| PyTorch | 2.10.0 (custom wheel, sm_60-sm_100) |
| TensorFlow | 2.20.0 |
| cuDF | 26.2.1 |
| cuML | 26.2.0 |
| CuPy | 14.0.1 |
ML packages: scikit-learn 1.6.1, xgboost 3.2.0, lightgbm 4.6.0, catboost 1.2.10, transformers 5.0.0, keras 3.13.2
Other packages: numpy 2.0.2, pandas 2.3.3, polars, jupyterlab 3.6.8, optuna, shap, opencv, albumentations, kaggle, kagglehub
DockerHub: gperdrizet/kaggle-nvidia
kaggle-cpu¶
| Component | Version |
|---|---|
| Base image | python:3.12-slim |
| Python | 3.12 |
| PyTorch | 2.10.0 (CPU) |
| TensorFlow | 2.20.0 |
ML packages: scikit-learn 1.6.1, xgboost 3.2.0, lightgbm 4.6.0, catboost 1.2.10, transformers 5.0.0, keras 3.13.2
Other packages: numpy 2.0.2, pandas 2.3.3, polars, jupyterlab 3.6.8, optuna, shap, opencv, albumentations, kaggle, kagglehub
DockerHub: gperdrizet/kaggle-cpu
kaggle-mac¶
Native linux/arm64 image for Apple Silicon (M1/M2/M3). No Rosetta emulation. GPU acceleration is not available inside Docker on macOS.
| Component | Version |
|---|---|
| Base image | python:3.12-slim |
| Platform | linux/arm64 |
| Python | 3.12 |
| PyTorch | 2.10.0 (CPU, ARM64) |
| TensorFlow | 2.20.0 |
ML packages: scikit-learn 1.6.1, xgboost 3.2.0, lightgbm 4.6.0, catboost 1.2.10, transformers 5.0.0, keras 3.13.2
Other packages: numpy 2.0.2, pandas 2.3.3, polars, jupyterlab 3.6.8, optuna, shap, opencv, albumentations, kaggle, kagglehub
DockerHub: gperdrizet/kaggle-mac