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Kumar Varma  • Peerlist

Build a dynamic digital portfolio and resume that stay in sync. Showcase your skills, projects, startups, and achievements.

Digiresume

built an Exam Portal using Next.js, Prisma, PostgreSQL (Neon), and NextAuth, where users can register, log in, and take exams seamlessly. The platform allows users to access various exam categories, attempt quizzes, and view their results. I implemented secure user authentication with NextAuth and optimized database interactions with Prisma and PostgreSQL to handle large volumes of data efficiently. The project provides a user-friendly interface for exam-taking while ensuring performance and security. Github Repo: https://github.com/Prasad48432/ExamPortal-NextAuth-Prisma

Exam Portal

a complete fully functional Gym Management app Subscriptions | Personal Training | Advanced Alerts | Growth Analyisis | Income Analysis used ( Flutter + Firebase + Firebase ) Cloud Functions for the app

Gym Management App

LinkFolio is a personal portfolio and link-in-bio web app that allows users to showcase their work, projects, and online presence in a clean, responsive layout. Designed for creators, freelancers, and professionals, LinkFolio helps you organize links, add project highlights, and share social media profiles — all in one customizable page. Built with modern web technologies, it’s optimized for both desktop and mobile viewers. Github Repo: https://github.com/Prasad48432/linkfolio

Linkfolio

Polyfjord, a YouTuber known for his tutorials on Graphic Design, 3D, and Sound Design, has created a beautiful personal showcase website using Next.js. This site highlights his work, providing a visually engaging platform to display his creative projects, tutorials, and expertise. The website reflects his design philosophy and serves as both a portfolio and a hub for his online presence.

Personal Website For Polyfjord

Sign Language Detection Using Computer Vision and Machine Learning, which focuses on bridging the communication gap between sign language users and non-signers. By leveraging advanced deep learning and computer vision, we developed a system that translates American Sign Language (ASL) gestures into both text and speech in real-time.