Deploying an end-to-end ml/dl model (for predicting maintaince for aircrafts by using dataset provided by NASA) into cloud server using Flask and Docker with CI/CD pipeline
This project promulgates a pipeline that trains an end-to-end predection model for aircraft maintanace using inputs, experiments by logging the model artifacts, parameters and metrics, build them as a web application followed by dockerizing them into a container and deploys the application containing trained model artifacts as a docker container into the cloud server with CI/CD integration, automated tests and releases.
