Vignesh P

Coimbatore

Summary

Highly motivated and ambitious, aspiring full-stack developer with a strong foundation in web development technologies. Committed to continuous learning and eager to contribute to a dynamic environment. Passionate about building user-centric and seamless web solutions. Experienced as a Software Developer Trainee with hands-on exposure to real-world projects. Successfully completed MERN stack training, enhancing proficiency in modern web technologies. Ready to take on new challenges and prove my capabilities in a professional setting.

Overview

Certification

Work History

Data Annotator

Objectways Technologies

Coimbatore

Performed data annotation and labelling tasks to support the training of machine learning models, focusing on various text and image data.
Annotated images with LiDAR 3D point data for computer vision tasks, ensuring precise and accurate labelling for object detection models.
Worked closely with cross-functional teams to ensure data quality and accuracy in support of the development of AI-based machine learning models.
Verified and validated labelled data to ensure it met project requirements and quality standards.

Software Developer Trainee

Aerele Technologies Private Limited

Tiruppur

Developed and maintained web applications using Frappe Framework as part of various projects within the ERPNext ecosystem.
Contributed to an internal project focused on Tally migration, where we designed and implemented a web page in React.JS to facilitate the import of Tally data into ERPNext.
Assisted in the face recognition attendance system using the DeepFace library in Python, integrated within Frappe, to store employee attendance data effectively.

Education

Bachelor of Engineering - Computer Science And Engineering

Kumaraguru College of Technology

Coimbatore, India

01-2022

Skills

Python
MySQL
HTML
CSS

Javascript
React JS
Frappe
Git and github

Certification

Completed Full Stack Development[MERN] at KGiSL Micro College

Soft Skills

Quick Learner
Adaptability

Projects

Face Recognition Attendance System

Developed a web-based Face Recognition Attendance System using the DeepFace library in Python.
Implemented VGG-Face and FaceNet models for accurate face detection and verification.
Successfully tested for future applications, including a QR code-based marriage event system, where attendees can scan a QR code, upload their photo, and retrieve event pictures featuring them.

Library Management System

Tech Stack: React.js, Node.js, Express.js, MySQL

Developed a full-stack web application for managing library operations including book inventory, user registrations, borrow/return logs, and admin controls.
Implemented RESTful APIs using Node.js and Express.js to handle user authentication, book issuance, and data updates securely.

Timeline