borysjas/ucla-ds-ml-base repository overview

⁠A basic data science and machine learning environment for research and personal experimentation.

Built on top of continuumio/miniconda3 with jupyter lab running out of the box (exposing port 8888).

Run docker, open your browser and you have access to an isolated portable environment with a terminal and an IDE.

Uncompressed, it's around 4.15GB large.

⁠Comes with:

• python 3.11 (just in case you want to install Tensorflow later)
• jupyter and jupyter lab (basically replaces vscode for development with a terminal in the browser; if you really don't like it, try code-server⁠ instead)
• the usual datascience packages: numpy, pandas, scikit-learn, networkx, igraph
• Spacy for NLP
• For plotting and interactive viewing: matplotlib, seaborn, plotly, pygwalker
• Torch with torchvision, torchtext, torchaudio and keras-core for ML (+ h5py)
• reservoirpy⁠ (built on top of pytorch) for reservoir-based machine learning.

⁠Example docker command to run

docker run --rm -p 8888:8888 -d borysjas/ucla-ds-ml-base 

Don't forget to add a volume or mount a binding⁠ to have permanent storage.

⁠How to use?

Open your web browser and go to http://localhost:8888/lab⁠?