What's App Clone

Developed a WhatsApp clone using React Native and Firebase as the backend by first setting up a new React Native project. Utilize Firebase's Authentication service for user registration and login functionalities, enabling users to create accounts and access the app securely. Implement Firebase's Realtime Database to handle real-time messaging between users, storing and retrieving messages as needed. Finally, design and style the user interface to resemble the WhatsApp messaging experience, allowing users to chat seamlessly within the app.

College Events

Develop a college event website using HTML, CSS, and JavaScript as the frontend technologies, utilizing Bootstrap for responsive design and layout. Integrate Firebase as the backend to handle user authentication, event registration, and data storage for a seamless user experience. Implement a user-friendly interface showcasing upcoming events, event details, and a registration form, making it easy for students and participants to stay updated and engaged with college activities.


In this AI-powered Pacman routing project, Python will be utilized to create a smart algorithm based on graph theory. The AI agent will navigate through the Pacman maze using graph-based search algorithms such as Breadth-First Search or A* Search to find the most efficient routes to reach the food pellets while avoiding ghosts. By employing advanced graph algorithms, the AI-driven Pacman will showcase intelligent decision-making capabilities, providing an exciting demonstration of how artificial intelligence can optimize gameplay and solve complex problems.


Created Uber-clone using React Native, Redux, Tailwind CSS, and Google Autocomplete allows users to request rides, view available drivers, and track their journey in real-time. With Redux managing the app's state, users can enjoy a seamless and responsive experience while interacting with the user-friendly UI powered by Tailwind CSS. The integration of Google Autocomplete ensures efficient address input, making it convenient for users to set their pickup and drop-off locations accurately.

Resume Parser

Developed a resume parser using Natural Language Processing (NLP) techniques in Python. The resume parser was capable of extracting relevant information, such as contact details, education history, work experience, skills, and certifications, from resumes in various formats (e.g., PDF, DOCX). Leveraging NLP libraries and machine learning algorithms, the parser intelligently analyzed the text, which ultimately should help HR professionals and recruiters to efficiently process and filter large volumes of resumes, streamlining the candidate selection process and enhancing recruitment efficiency.

Spotify Recommendation System

Created advanced algorithm for a Spotify recommendation system by analyzing user listening patterns, preferences, and behavior. Leveraging machine learning techniques, the algorithm will process vast amounts of data to suggest personalized playlists, songs, and artists to users based on their individual tastes, improving overall user engagement and satisfaction with the platform. Through continuous learning and optimization, the recommendation system will enhance music discovery, creating a tailored and enjoyable listening experience for Spotify users.