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MLOPS

Complete Automation of ML/DL model using Jenkins & Docker

Most important thing to keep in mind is to change the names of the files after pull.

  • Dockerfile(ml) -> Dockerfile
  • Dockerfile(dl) -> Dockerfile

Keep the 2 files in 2 seperate folders and create the image.

  • train(ml).py -> train.py
  • train(dl).py -> train.py

This is so because we will provide environment per code basis, so in one go only 1 file goes to the environment.

This is a detailed article on the setup I have made =>

https://medium.com/@daksh.jain00/complete-automation-of-ml-dl-model-using-jenkins-docker-ae72e365fd99

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