My Docker-based AI/ML Training Environment

Dive into Docker, JupyterLab, and machine learning with 'learning-python'. Features Python 3.9, NodeJS, and PostgreSQL with pgvector. Start with make start at localhost:8888.

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Apr 14, 2024 • 1 min read

Photo by Andrea De Santis / Unsplash

Without further ado, here is the link to the GitHub project I've created to stretch my muscles into Machine Learning, Artificial Intelligence, and Python:

Run that on your computer, or spin it up as a GitHub Space. It works both ways.

You get:

A JupyterLAB server with its web interface on localhost:8888 running Python 3.9 and NodeJS 20.x kernels
A Postgres DB with pgvector already installed
A Docker Compose project that spins up containers
A Makefile interface to operate the project

You need:

Docker and Docker Compose

Here are a few high-level commands to operate with the environment:

# Start the services
make start

# Stop the services
make stop

👉 Once the environment start, open your browser to http://localhost:8888

Managing Dependencies

As this thing works inside a Docker container, you will need to modify the relative Dockerfile in order to install dependencies for Python or NodeJS.

Open .jupiter/Dockerfile with your favourite editor.
Search for "Python Dependencies" or "Node Dependencies"
Add what you need
run the following command:

# Install the dependencies and restart the environment
make reset

Managing Dependencies

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