Found 102 repositories(showing 30)
Machine Learning Patient Risk Analyzer Solution Accelerator is an end-to-end (E2E) healthcare app that leverages ML prediction models (e.g., Diabetes Mellitus (DM) patient 30-day re-admission, breast cancer risk, etc.) to demonstrate how these models can provide key insights for both physicians and patients. Patients can easily access their appointment and care history with infused cognitive services through a conversational interface. In addition to providing new insights for both doctors and patients, the app also provides the Data Scientist/IT Specialist with one-click experiences for registering and deploying a new or existing model to Azure Kubernetes Clusters, and best practices for maintaining these models through Azure MLOps.
luongphambao
No description available
CornelliusYW
MLOps implementation for Diabetes prediction
rayluo88
This project implements a comprehensive MLOps solution for predicting diabetes onset using the UCI ML Diabetes dataset.
vipunsanjana
MLOps-ready Diabetes Prediction API using FastAPI, Docker, and Kubernetes. Includes automated CI/CD with GitHub Actions, versioned Docker images, and secret management for secure deployments.
abhi227070
This project deploys a diabetes prediction model on AWS using MLOps principles. It features a Flask-based UI for user interaction and utilizes CI/CD pipelines for automated deployment. By leveraging AWS infrastructure, the project ensures scalability, version control, and monitoring of the deployed model.
LohithUnnam
This comprehensive MLOps project focuses on Diabetes Prediction and utilizes a range of tools, including Prefect, MLflow, FastAPI, and Streamlit.
Abhishek28k
No description available
QuyDatSadBoy
No description available
ELYAZID-bit
No description available
Abhi-mishra998
No description available
Ahmed-Rizk1
No description available
harshaRedE31
No description available
guthayaswanth0123
End-to-end ML and MLOps pipeline for Diabetes Prediction including model training, FastAPI API serving, Docker containerization, and production-ready deployment workflow
mauseoluwasegun
End-to-End MLOps Pipeline for Disease Prediction Description: A complete production workflow demonstrating the lifecycle of a machine learning application. Features a Scikit-learn random forest model wrapped in a FastAPI microservice, containerized with Docker, and configured for scalable deployment on Kubernetes
Monica-Ashok
This repository is a curated collection of evolving machine learning projects—from bite-sized real-world use cases like diabetes prediction to more advanced pipelines integrating MLOps workflows. Every weekly build is crafted to deepen understanding, spark creative experimentation, and push the boundaries of applied AI.
kjgood99-pong
MLOps PIMA_Diabetes_Prediction
George-Pustovit
MLOps pipeline for diabetes prediction
Sh123-max
Diabetes prediction using mlops (agp methodology)
arunmohapatra
diabetes-prediction bits MLOps Assignment -1
JawadAmin
MLOps Implementation using Python for Diabetes Prediction
Abhishek-Sengupta
This is a MLOps project for Diabetes prediction using Classification
YogitaGour
The task involves creating automated test scripts using the Playwright framework for testing various functionalities of the Amazon.com website
risearch
Diabetes Prediction Model – MLOps Project (FastAPI + Docker + K8s)
baolongbk29
No description available
TanishqThuse
🚀 End-to-End MLOps and Cloud Computing project that integrates Machine Learning with FastAPI, Docker, Kubernetes, and React. This system predicts diabetes in real time using a trained Random Forest model and demonstrates full lifecycle deployment — from model training and containerization to cloud-ready API hosting and interactive UI.
doyindevops
No description available
kkbejoy
No description available
giacuong171
No description available
DarylAdrien
No description available