AI/ML Workflows with GitHub Actions

2.1 Workflows

A workflow is a configurable automated process made up of one or more jobs. It’s defined in a YAML file located in the `.github/workflows` directory.

2.2 Jobs

Jobs are individual tasks that are executed as part of a workflow. Each job runs in a fresh instance of a virtual environment.

2.3 Actions

Actions are the smallest building blocks of a workflow. They can be custom or third-party actions and encapsulate a piece of functionality.

3.1 Define the Workflow

Create a new file named `ml-workflow.yml` in the `.github/workflows` directory.

3.2 Set Up the Trigger

Use triggers like `push` or `pull_request` to start the workflow.

3.3 Define Jobs and Steps

Each job can have multiple steps, and you can define them as follows:

jobs:
  build:
    runs-on: ubuntu-latest
    steps:
      - name: Checkout code
        uses: actions/checkout@v2
      - name: Set up Python
        uses: actions/setup-python@v2
        with:
          python-version: '3.8'
      - name: Install dependencies
        run: |
          pip install -r requirements.txt
      - name: Run training
        run: |
          python train.py
      - name: Deploy model
        run: |
          python deploy.py
            

3.4 Monitor Workflow

Monitor the execution of your workflow through the Actions tab in your GitHub repository.

4.1 Sample YAML Workflow

name: CI for ML Models

on:
  push:
    branches:
      - main

jobs:
  train:
    runs-on: ubuntu-latest
    steps:
      - name: Checkout code
        uses: actions/checkout@v2
      - name: Set up Python
        uses: actions/setup-python@v2
        with:
          python-version: '3.8'
      - name: Install Dependencies
        run: |
          pip install -r requirements.txt
      - name: Run Training
        run: |
          python train.py
      - name: Run Tests
        run: |
          pytest tests/