https://github.com/sayamalt/airline-passenger-satisfaction-classification
Successfully developed a machine learning model to predict Airline Passenger Satisfaction by building an end-to-end MLOps pipeline. It integrates DVC for data versioning, a Dockerfile for containerization, and CI/CD using GitHub Actions for automated deployment.
https://github.com/sayamalt/airline-passenger-satisfaction-classification
azure-web-app-service ci-cd-pipeline classification docker-container dvc-pipeline experiment-tracking exploratory-data-analysis feature-engineering github-actions hyperparameter-tuning machine-learning mlflow mlflow-tracking mlops-workflow model-registry model-training-and-evaluation model-versioning optuna scikit-learn
Last synced: 17 days ago
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Successfully developed a machine learning model to predict Airline Passenger Satisfaction by building an end-to-end MLOps pipeline. It integrates DVC for data versioning, a Dockerfile for containerization, and CI/CD using GitHub Actions for automated deployment.
- Host: GitHub
- URL: https://github.com/sayamalt/airline-passenger-satisfaction-classification
- Owner: SayamAlt
- Created: 2024-11-30T07:50:08.000Z (5 months ago)
- Default Branch: main
- Last Pushed: 2024-12-03T08:42:52.000Z (5 months ago)
- Last Synced: 2025-02-11T12:26:46.059Z (2 months ago)
- Topics: azure-web-app-service, ci-cd-pipeline, classification, docker-container, dvc-pipeline, experiment-tracking, exploratory-data-analysis, feature-engineering, github-actions, hyperparameter-tuning, machine-learning, mlflow, mlflow-tracking, mlops-workflow, model-registry, model-training-and-evaluation, model-versioning, optuna, scikit-learn
- Language: Jupyter Notebook
- Homepage: https://airline-passenger-satisfaction-akevhzeuh8btgffr.canadacentral-01.azurewebsites.net/
- Size: 53.5 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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