gperdrizet/datascience-mac repository overview

⁠Data science Mac (ARM64) development container

Native ARM64 data science environment for Apple Silicon (M1/M2/M3) Macs. Runs without Rosetta emulation in Docker Desktop. Covers intro Python, data visualization, data cleaning, feature engineering, and traditional machine learning.

⁠1. Features

• Python 3.12
• JupyterLab
• scikit-learn, XGBoost, statsmodels
• pandas, numpy, scipy
• matplotlib, seaborn, plotly
• optuna (hyperparameter optimization)
• linux/arm64, native Apple Silicon, no Rosetta

⁠2. Usage with VS Code

Start the container, then use VS Code's Dev Containers: Attach to Running Container command to connect:

docker run --rm -it \
  -v $(pwd):/workspace \
  gperdrizet/datascience-mac:latest \
  /bin/bash

Open the Command Palette (Ctrl+Shift+P), run Dev Containers: Attach to Running Container, and select the container.

⁠3. Running directly with Docker

docker run --rm -it \
  -p 8888:8888 \
  -v $(pwd):/workspace \
  gperdrizet/datascience-mac:latest \
  jupyter lab --ip=0.0.0.0 --no-browser --allow-root

⁠4. Requirements

• Docker Desktop for Mac (Apple Silicon)

⁠5. License

MIT. See docker-images⁠.