RESTful API für Todo-Management mit User- und Gast-Sessions, entwickelt mit Express.js und MariaDB.
RESTful API für Todo-Management mit User- und Gast-Sessions, entwickelt mit Express.js und MariaDB.
A scalable microservices architecture with NestJS, Kafka, and Docker, featuring decoupled services (customer, transaction, notification) on IBM Cloud Code Engine. Includes CI/CD (GitHub Actions), secure Kafka brokers, fault tolerance, cloud-native design, and real-time notifications.
Houses Github actions to generate C# code from Avro schemas and pack them as a NuGet package
An electron desktop app which automates 20+ remote tutors zoom session based on their main/overtime schedules, eliminating session delays by 99.9%. 🦏
Conference Publishing System is a web platform developed to support the editorial and publishing process for academic conference proceedings. The project was inspired by Open Journal Systems, but aims to address its shortcomings and adapt it to the actual workflow of academic publishing in universities.
An Ai powered assistant trained in good decision making on how to track the female period cycle
HiLink is a dynamic and user-friendly hiking website designed with Next.js, offering seamless navigation, responsive design, and fast load times. Customize your experience with tailor-made templates while ensuring secure and reliable access to hiking resources.
An Frontend made in Nextjs for Library Management System
The Solar Company e-commerce website is built using Next.js and provides an intuitive platform for users to explore and purchase solar products. With a focus on sustainability, the site offers a seamless shopping experience with features like product browsing, secure checkout, and responsive design.
Quality check list management for each stage of production (manufacturing)
This project is a Flask-based web application designed to predict students' performance based on various input features. It integrates a machine learning pipeline to analyze user-provided data, preprocess it, and predict outcomes, offering an intuitive interface for end-users.
This project is a machine learning application that predicts emotions from text input. It consists of a trained model that can classify text into different emotion categories and a FastAPI-based REST API for serving predictions.
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