CI/CD for Machine Learning
Ravi Bhadauria
Machine Learning Engineer
${{ context.XXX }}github: information about the workflow runenv: variables set in the workflowsecrets: names and values that are available to workflowjob: info about the current jobrunner: info about the machineenv keyenv context as ${{ env.ENV_VAR }}name: Greeting on variable day # Global env env: Greeting: Hellojobs: greeting_job: runs-on: ubuntu-latest # Local env: scoped to greeting_job env: First_Name: Ravisteps: - run: | echo "${{ env.Greeting }} \ ${{ env.First_Name }}."
secrets context${{ secrets.SuperSecret }}steps: - name: Hello world action env: # Set the secret as an env var super_secret: ${{ secrets.SuperSecret }}with: # Or as an input super_secret: ${{ secrets.SuperSecret }}
Printing secret
steps:
- name: Print secret
run: |
echo "my secret is \
${{ secrets.SuperSecret }}"
Output




${{ secrets.GITHUB_TOKEN }}permissions:
pull-requests: write
permissions:
pull-requests: write
steps:
- name: Comment PR
uses: thollander/actions-comment-pull-request@v2
with:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
message: |
Hello world ! :wave:

CI/CD for Machine Learning