Django-based text utility service, offering multi-language translation, sentiment analysis, and text summarization, all seamlessly deployed on AWS Lambda with Docker for robust and scalable performance.
- Updated
Jul 31, 2024 - JavaScript
Django-based text utility service, offering multi-language translation, sentiment analysis, and text summarization, all seamlessly deployed on AWS Lambda with Docker for robust and scalable performance.
Headless Ecommerce Medusa Backend Deployment on AWS (ECS + Terraform + Docker + GitHub Actions)
This repository contains the frontend, backend and Docker and Jenkinsfile for the Smart India Hackathon 2023 finals. The problem statement it solves is "Integration of different databases and retrieving relevant information based on the prompt entered in NLP"
Built a machine-learning system to predict customer interest in vehicle insurance using demographic and behavioral data. Containerized and deployed the model as a web service with a full CI/CD pipeline.
The Kidney Disease Classification project is a comprehensive machine learning pipeline designed to classify kidney disease using advanced tools like MLflow and DVC. It emphasizes reproducibility, scalability, and deployment readiness. The project leverages a modular design, enabling efficient experimentation and deployment in cloud environments.
sample node.js app to build and push to aws ECR
This repository focuses on improving the efficiency and sustainability of heavy-duty vehicles by accurately predicting failures in the Air Pressure System (APS) and reducing the cost of unnecessary repairs.
The repository contains definitions of FLUX. In the repository, you'll find a definition of a simple application and ImageUpdateAutomation, ImagePolisy to automatically download new image tags from Amazon ECR and update the application definition in this repository.
Manas is a web application that provides disease predictions using NLP and a portal for organ donation and recipient details.
End-to-end ML project predicting student math scores using demographic and academic data. Includes data pipelines, model training, Flask web app, and AWS EC2 deployment with Docker & CI/CD. Integrated logging, exception handling, and modular pipelines for production readiness.
Add a description, image, and links to the awsecr topic page so that developers can more easily learn about it.
To associate your repository with the awsecr topic, visit your repo's landing page and select "manage topics."