This repository contains instructions, template source code and examples on how to serve/deploy machine learning models using various frameworks and applications such as Docker, Flask, FastAPI, BentoML, Streamlit, MLflow and even code on how to deploy your machine learning model as an android app.

Zero Trust AI 360

app that performs emotion recognition - easy to fork and experiment with 😇

The source for Pachyderm's documentation site.

Aircraft components are susceptible to degradation, which affects directly their reliability and performance. This machine learning project will be directed to provide a framework for predicting the aircraft’s remaining useful life (RUL) based on the entire life cycle data in order to provide the necessary maintenance behavior.

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

Implemented a wine quality prediction project using MLOps and MLflow. Utilized the Wine Quality dataset, developed machine learning models, and deployed them on an EC2 instance. This project aimed to gain hands-on experience in MLOps principles and the effective use of MLflow for model tracking and deployment.

This project focuses on predicting wine quality using regression models.

🐳 comprehensive guide to Docker, understand containerization concepts. Ideal for both beginners developers looking to enhance their Docker skills.

Training and deploying LightGBM Model with MLFlow, fastapi, App Engine and github actions

Deploy a computer vision model trained to detect common objects in pictures

✅ Spell Correction with MLOps project utilizes machine learning techniques to automatically correct spelling errors in text side by side.

Slides for ML deployment and MLOps

Matt Edwards | Data Scientist | Huntsville AL

An End-to-End production ready application for predicting the quality of wine🍇. Build ML model and deployed using flask 🤖. Used various MLOps tools to smooth the workflow.

End to End MLops with Mlflow project with Github actions and docker image

Training and deploying CatBoost Model with MLFlow, Flask, AWS ECS and github actions

This project is about the prediction of red wine quality using different machine learning algorithms with MLOps and CICD pipeline.