Fast model deployment on any cloud 🚀

Instructions to deploy django, django channels to AWS

Django eCommerce website with a lot of advanced custom functionalities, RDS Postgres and deployed it on Amazon AWS

Deploy a scalable and secure Django blog on AWS! This project harnesses the power of AWS services like EC2, RDS, S3, DynamoDB, CloudFront, and Route 53 to create a robust web application. Users can seamlessly upload pictures and videos on their blog pages, with media content stored in an S3 bucket and metadata recorded on a DynamoDB table.

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.

ARCH and GARCH models along with MLOps pipeline using AWS platform to deploy model in a production environment.

Developed an image classification web app using CNN to differentiate cats and dogs. Achieved high accuracy, precision, recall, and F1 score. Pipeline involves data preprocessing, model training, Docker deployment on AWS ECS, user-friendly interface, and reliable CI/CD. Showcases deep learning's potential in image analysis.

Troposphere and shellscript based AWS infrastructure automation creates an awsapigateway lambda with a go backend

🕐 ⌚ This is a javascript application. The application consists of a responsive digital clock.

Search relevancy algorithm for news articles using Sentence-BERT model and ANNOY library along with deployment on AWS using Docker.

Unleash the Power of Music with Personalized Concert Recommendations.

nlp text mining dashboard to extract most used keywords on software engineering and data science articles. Tech Stack: Django, Python, PostgreSQL, HTML/CSS, JavaScript, Docker, AWS

This is my test cloud application that displays a login page and once logged in displays a list of orders. (Cloud Platforms: Heroku, Azure, AWS & Google Cloud)

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QA DevOps Assessment

An AWS saas starter app using typescript, python and terraform

𝗠𝗟 𝗽𝗿𝗼𝗷𝗲𝗰𝘁, encompassing key topics like 𝗗𝗮𝗴𝘀𝗵𝘂b and 𝗠𝗟𝗳𝗹𝗼𝘄 for version control, 𝗠𝗟𝗢𝗽𝘀 practices for efficient deployment, and robust 𝗖𝗜/𝗖𝗗 𝗽𝗶𝗽𝗲𝗹𝗶𝗻𝗲 setup. Showcased 𝗔𝗪𝗦 𝗱𝗲𝗽𝗹𝗼𝘆𝗺𝗲𝗻𝘁 with the help of 𝗚𝗶𝘁𝗛𝘂𝗯 𝗔𝗰𝘁𝗶𝗼𝗻 prowess for seamless machine learning application integration.

Employee login system using facial recognition

Refactory Final

A Transmission Control Protocol (TCP) chat app created using Node.js, using the readline module to interact with the Command Line Interface (CLI) for chats. Deployed on AWS.