Nerdward/Mlops_project
An end to end ML project. Using MLflow for experiment tracking and model registry. Prefect for workflow orchestration. S3 for artifacts storage. AWS Lambda/ ECR for serverless model serving. AWS REST API gateway as endpoint to lambda function. GitHub Actions for CI/CD.
This project helps a real estate company predict house prices based on various property features like the number of bedrooms and porch size. It takes raw property data as input and outputs a predicted house price. The primary users are machine learning engineers who need to build, track, and deploy predictive models for real estate valuation.
No commits in the last 6 months.
Use this if you are a machine learning engineer working for a real estate company and need a robust system to predict house prices, manage experiments, and deploy models efficiently.
Not ideal if you are looking for a simple, off-the-shelf house price prediction tool without the need for custom model training, experiment tracking, or infrastructure management.
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Last pushed
Sep 11, 2022
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