gperdrizet/deeplearning-mac repository overview

⁠Deep learning Mac (ARM64) development environment

A ready-to-use deep learning environment for Apple Silicon Macs (M1/M2/M3). Includes both PyTorch and TensorFlow frameworks. Built as a native linux/arm64 image — runs in Docker Desktop without Rosetta emulation.

⁠1. Features

• Dual framework support: Both TensorFlow 2.17 and PyTorch (CPU) pre-installed
• Native ARM64: No Rosetta emulation — runs at native speed on Apple Silicon
• VS Code Dev Container ready: Pre-configured vscode user for seamless devcontainer integration

⁠2. Included software

⁠2.1. Additional Python packages

• jupyterlab - Notebook interface
• pandas - Data manipulation
• scikit-learn - Machine learning utilities
• scipy - Scientific computing
• matplotlib - Data visualization
• seaborn - Statistical data visualization
• tensorboard - Training visualization
• keras_tuner - Hyperparameter tuning for Keras
• optuna - Hyperparameter optimization framework
• ipywidgets - Interactive widgets for Jupyter

⁠3. Usage with VS Code Dev Containers

This image is designed for use with the deeplearning-devcontainer⁠ repository, which provides ready-to-use VS Code Dev Container configurations. The vscode user (UID 1000) is pre-configured with sudo access for a seamless development experience.

⁠4. Running directly with Docker

docker run --rm -it \
  --platform linux/arm64 \
  -p 8888:8888 \
  -v $(pwd):/workspace \
  gperdrizet/deeplearning-mac:latest \
  jupyter lab --ip=0.0.0.0 --no-browser --allow-root

⁠5. Requirements

• Docker Desktop for Mac (Apple Silicon)

⁠6. License

See the GitHub repository⁠ for license information.