Source: medium.com
MLOPS, Integrating ML with DevOpsCategory: Software, Jenkins, github, machine-learning
Create a container image that has Python3 and Keras or numpy installed using Dockerfile Job2: By looking at the code or program file, Jenkins should automatically start the respective machine learning software installed interpreter install image container to deploy code and start training( eg.
In Build, select Execute shell to perform following commands which will create a directory in the container and copy all the files from the GitHub repo to this directory
In Build, select Execute shell for performing this script which will autodetect the respective machine learning software installed interpreter install image container and launch the Docker container according to the model
In Build, select Execute shell for performing this script which will train the machine learning or deep learning model until the accuracy is greater than 80% of the model and after training store the output in a output.txt file
In Build, select Execute shell to perform following commands which will create a directory in the container and copy all the files from the GitHub repo to this directory
In Build, select Execute shell for performing this script which will autodetect the respective machine learning software installed interpreter install image container and launch the Docker container according to the model
In Build, select Execute shell for performing this script which will train the machine learning or deep learning model until the accuracy is greater than 80% of the model and after training store the output in a output.txt file
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