awsecr

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.

An AI-powered blog that automatically generates and publishes new articles every day.

Automated CI/CD pipeline using GitHub Actions, Docker, Terraform & AWS EC2

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.

TodoBunny is a lightweight, user-friendly To-Do list application built with React and Vite. It allows users to add and delete tasks with a clean, modern interface.

To deploy a trained Machine Learning model on AWS using Docker containers, with Terraform managing all infrastructure (compute, storage, permissions, networking).

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"

Experience seamless deployment with our cutting-edge platform. Zero configuration, maximum performance.

The repository contains the terraform code needed to create kubernetes clusters in Amazon Elastic Kubernetes Service and Amazon Elastic Container Registry image storage.

Glassdoor_dataScience_jobs project is a compact end-to-end FastAPI-based pipeline for ingesting, validating, transforming, training, and serving machine-learning models on job-posting data. It combines reproducible ML runs, containerized deployment, and CI/CD to streamline model development and production inference.

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 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

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.

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.