This Chrome extension analyzes the first 20 comments on a YouTube video to provide an overview of the audience's sentiment. It categorizes comments as positive, negative, or neutral, giving users a quick and easy way to gauge viewer reactions.

This project is a plant disease classification and diagnosis system that uses a neural network to classify plant disease images. It utilizes the Plant Village dataset for training and offers two backend options: Django and FastAPI. Additionally, a Flutter app is provided for users to upload images of plant leaves and identify the disease.

As a Machine Learning Research Intern, I investigated the influence of Data Pre-Processing on machine learning model performance. Using a publicly available dataset from Huawei's Speed Video Global Operating Platform, I applied Sklearn, Pandas, Numpy, and Matplotlib for pre-processing and prediction. The project revealed critical insights into the impact of data quality on machine learning outcomes, enhancing my practical skills and contributing to the field's knowledge.

In collaboration with two team members, I took on the challenge of enhancing the user interface (UI) of the official Ecell app. Our primary focus was to revamp the existing UI to create a more engaging and user-friendly experience. Additionally, we successfully implemented a dynamic quizzing system, adding an interactive element to the app's features. Through active collaboration and dedicated efforts, our team achieved significant improvements in the overall UI, making the Ecell app more intuitive and enjoyable for its users.

I teamed up with a friend to spearhead the development of the official app for Eclectika, our cultural fest. My major contribution involved conceiving and implementing a captivating dinosaur-themed user interface, infusing the app with a unique and visually appealing design. Leveraging the power of Firebase, I integrated authentication and real-time database functionalities to enhance the app's responsiveness and user engagement. The app was meticulously crafted to serve as a comprehensive resource, providing students with detailed event information for Eclectika. Our collaborative efforts resulted in the successful creation of an interactive and informative platform, enriching the overall experience for participants and attendees of the cultural fest.

ESOW: Electronic Safety Of Women, a dynamic app developed with Flutter and Firebase, is designed to empower women in emergencies. Its standout feature allows users to send emergency messages with live location coordinates to selected contacts. For added security, the app enables the sharing of live location with up to five contacts. Experience enhanced safety with ESOW at your fingertips.

Presenting our backend project tailored for the Robotix Club, featuring a Django Rest Framework implementation. This dynamic backend seamlessly integrates project posting, liking, commenting, and verification functionalities through Restful APIs. Crafted specifically for the Robotix Club, this project enhances collaboration and engagement within the club's community. Experience a user-friendly environment where members can effortlessly share, appreciate, and discuss projects. The added verification feature ensures the credibility of project information, contributing to a trustworthy platform.