Maternal Health Risk prediction MLOps pipeline
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Updated
Dec 6, 2022 - Python
Maternal Health Risk prediction MLOps pipeline
Final Project of the MLOps Zoomcamp hosted by DataTalksClub.
Online Prediction Machine Learning System designed, deployed and maintained with MLOps Practices. Goal of the project is to predict individuals income based on census data.
MLOps Zoomcamp hosted by DataTalksClub.
This an attempt to predict fraud transactions from a huge collection of records of bank transaction over a period of time.
Learn how to handle model drift and perform test-based model monitoring
This project builds an MLOps pipeline using Evidently for monitoring model performance and Prefect for task orchestration. It processes NYC taxi data, stores metrics in PostgreSQL, and visualizes results in Grafana via Docker Compose.
🌎 🚙📚 Predicting travel times and traffic density on a highway in Slovenia
Development, deployment and monitoring of machine learning models following the best MLOps practices
Build End to End ML pipeline for USVisa prediction, deploy web App to AWS Ec2 instance using Docker, CI/CD with github actions
This project adopts a modular Python architecture within an MLOps framework to enhance subscription renewal predictions, utilizing FastAPI and MongoDB with AWS integration (S3, ECR, EC2). Docker ensures seamless deployment, and GitHub Actions automate the CI/CD workflows. Evidently AI monitors drift to guarantee predictive accuracy and reliability.
Comparison between several Python data profile libraries.
Evidently AI in tracking, analyzing, and visualizing machine learning model performance and data drift ensure their reliability over time.
An end-to-end machine learning project predicting DoorDash delivery durations, utilizing MLOps principles and best practices.
White and Red Wine classification using logistic regression
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