Project 📁

Projects

Technologies: React.js, Sass, Express.js, MongoDB, Axios, Nodemailer, Multer | Link

Engineered a robust file-sharing application featuring seamless file upload, secured sharing, and reliable email notifications for improved data management.
Orchestrated file deletion automation using cron jobs, scheduling tasks to remove files every 24 hours, which led to a 25% reduction in server storage costs and enhanced operational performance.
Implemented a secure and scalable backend using Express.js and MongoDB to handle large volumes of file uploads and downloads.
Designed a responsive and intuitive user interface with React.js and Sass to enhance user experience.
Utilized Nodemailer to send automatic email notifications for file sharing, ensuring timely communication between users.
Integrated Multer for efficient file handling and management on the server side.

Technologies: React.js, Socket.io, Express.js, Tailwind CSS, Vite | Link

Spearheaded the development of an interactive pair programming platform with real-time collaboration, code sharing, chat functionality, and file downloads, featuring an intuitive user interface for enhanced programming experience.
Achieved real-time code synchronization, maintaining latency below 92 ms for up to 100 concurrent users.
Enabled real-time code collaboration using Socket.io, allowing users to code together seamlessly.
Developed a chat feature to facilitate communication between users during pair programming sessions.
Built the backend with Express.js to manage user sessions, authentication, and file handling.
Styled the application using Tailwind CSS for a clean and modern look, ensuring an excellent user experience.
Optimized the development process with Vite, improving build times and overall performance.

Technologies: Python, NLP, Matplotlib, Streamlit, Spacy, Pandas | Link

Developed an NLP-based resume screening tool that ranks resumes, identifies the top 10% of candidates, and offers visual insights for efficient evaluation.
Integrated Spacy for advanced text processing, achieving a 97% accuracy rate in resume keyword extraction and scoring.
Implemented a ranking algorithm to sort and highlight the most relevant candidates based on predefined criteria.
Created interactive visualizations using Matplotlib to present data insights and support decision-making.
Built the user interface with Streamlit, allowing users to easily upload resumes and view analysis results.
Employed Pandas for data manipulation and analysis, ensuring accurate and efficient processing of resume data.