This is a containerized dev setup to work on machine learning problems using Anaconda with VSCode.
It installs conda/miniconda3:latest as a base image and installs ipykernel,
so it supports Jupyter notebooks (installed as a VSCode extension), as well as debugging *.py files directly.
A conda environment is created within the dev container and can easily be configured with the desired dependencies/packages. Various VSCode extensions are installed automatically in the container as well.
Mac OS Install Instructions:
- Install Docker Desktop
brew install --cask docker - Install VSCode
brew install --cask visual-studio-code - Open VSCode
- Install VSCode remote container extension: ms-vscode-remote.remote-containers
- Start dev container: F1 + "Open folder in container ..."
- Open demo.ipynb or demo.py to try the setup
Optional Steps:
- Add/remove VSCode extensions in .devcontainer/devcontainer.json
- Change Anaconda environment in .devcontainer/environment.yml
- Update gitignore to match your setup