datascience images¶
Lightweight data science environment for intro Python and ML courses. Three variants: NVIDIA GPU (with CuPy acceleration), CPU-only, and Apple Silicon.
datascience-nvidia¶
| Component | Version |
|---|---|
| Base image | nvidia/cuda:12.8.1-runtime-ubuntu24.04 |
| Python | 3.12 |
| CUDA | 12.8 |
| GPU support | Pascal-Blackwell (sm_60-sm_100) |
Packages: numpy, pandas, scipy, scikit-learn, xgboost, statsmodels, matplotlib, seaborn, plotly, jupyterlab, optuna, python-dotenv, cupy 13.6.0 (custom wheel)
DockerHub: gperdrizet/datascience-nvidia
datascience-cpu¶
| Component | Version |
|---|---|
| Base image | python:3.12-slim |
| Python | 3.12 |
Packages: numpy, pandas, scipy, scikit-learn, xgboost, statsmodels, matplotlib, seaborn, plotly, jupyterlab, optuna, python-dotenv
DockerHub: gperdrizet/datascience-cpu
datascience-mac¶
Native linux/arm64 image for Apple Silicon (M1/M2/M3). Docker Desktop on Mac runs it without emulation. GPU/Metal passthrough is not supported inside Docker on macOS.
| Component | Version |
|---|---|
| Base image | python:3.12-slim |
| Platform | linux/arm64 |
| Python | 3.12 |
Packages: numpy, pandas, scipy, scikit-learn, xgboost, statsmodels, matplotlib, seaborn, plotly, jupyterlab, optuna, python-dotenv
DockerHub: gperdrizet/datascience-mac