A guide to MLOps

A simple yet complete guide to MLOps tools and practices - from a conventional way to a modern approach of working with ML projects. Website available at https://mlops.swiss-ai-center.ch.

Local development with Docker Compose (recommended)

To improve the documentation locally, run Material for MkDocs with the following commands:

# Build the Docker container
docker compose build

# Start the Docker container
docker compose up serve

You can now access the local development server at http://localhost:8000.

If you make changes to the documentation, the web page should reload.

Local development with Python

To improve the documentation locally, run Material for MkDocs with the following commands:

# Install all dependencies for Material for MkDocs
sudo apt install --yes \
    libcairo2-dev \
    libfreetype6-dev \
    libffi-dev \
    libjpeg-dev \
    libpng-dev \
    libz-dev

# Create the virtual environment
python3.11 -m venv .venv

# Activate the virtual environment
source .venv/bin/activate

# Install the Python dependencies
pip install \
    --requirement requirements.txt \
    --requirement requirements-freeze.txt

# Run Material for MkDocs
mkdocs serve

You can now access the local development server at http://localhost:8000.

If you make changes to the documentation, the web page should reload.

Format the documentation with Docker Compose (recommended)

To format the Markdown documentation, run mdwrap with the following commands:

# Build the Docker container
docker compose build

# Start the Docker container
docker compose up format

Format the documentation with Python

To format the Markdown documentation, run mdwrap with the following commands:

# Create the virtual environment
python3.11 -m venv .venv

# Activate the virtual environment
source .venv/bin/activate

# Install the Python dependencies
pip install \
    --requirement requirements.txt \
    --requirement requirements-all.txt

# Run mdwrap
mdwrap --fmt docs