Developed the 'Reserve a Table' feature for the Little Lemon Website using React, effectively managing state with hooks such as useState.
Implemented advanced form handling methods, including controlled and uncontrolled components, alongside the useRef hook, to optimize the booking process.
Performed thorough unit testing with Jest, guaranteeing the functionality and dependability of components.

• Pioneered RESTful API implementation with Spring Boot for seamless frontend-backend communication, while enforcing Spring Security and employing MySQL for efficient backend management. • Orchestrated frontend development leveraging React, integrating Tailwind CSS and Material-UI (MUI) for UI design, Redux for state management, and JWT for secure authentication.

Led the creation of extensive frontend and backend components leveraging Python within the resilient Django Web Framework, following the Model-View-Template (MVT) architectural paradigm to ensure organized application design and upkeep. • Managed the deployment of the application on AWS via EC2 for hosting, employing RDS coupled with Postgres for efficient database administration, and S3 for the storage of static and media files. • Integrated dynamic content seamlessly using Django Template Language, Bootstrap, and HTML, crafting a responsive and visually captivating user interface to elevate user engagement.

Extracted actionable cryptocurrency market insights through large-scale NLP analysis (preprocessing, tokenization) of over 100k tweets, incorporating BERT models (FinBERT & CryptoBERT) for accurate sentiment classification.

Architected and developed a responsive Kotlin Android app utilizing OOPs and LiveData (20% reduced data latency). Implemented engaging bill-splitting & spending analysis features (coroutines) leading to a 15% user engagement rise.
Facilitated secure payment processing via PayPal integration, championed the use of GitHub for version control (reducing merge conflicts by 30%), fostering a collaborative development workflow.

Executed Expectimax algorithm for tree search AI in 2048 game, considering chance and limited depth search; algorithm optimized move selection, resulting in a 25% increase in game win rate.
Upgraded tree search with a neural network trained on game state data and projected utility values for each level.

This project analyzes the impact of Twitter sentiments on Google's stock prices using Afinn and Vader for sentiment analysis and integrates predictive modeling techniques, GANs and ARIMA, with Yahoo Finance data to forecast stock trends. The analysis provides insights into how public perceptions influence financial markets, serving as a bridge between social media sentiment and economic indicators.