Gen AI Project – Developed a smart, interactive chatbot capable of answering queries, explaining concepts, and acting as a learning assistant. – Applied prompt engineering techniques to generate accurate, context-aware responses using Large Language Models (LLMs). – Implemented conversation memory and context handling to enhance user interaction and continuity. – Integrated a user-friendly frontend interface and deployed the application for real-world usability. – Gained hands-on experience in Generative AI, problem-solving, and end-to-end project development.

Architected and developed a full-stack cross-platform application automating the complete machine learning lifecycle, from CSV data ingestion to neural network deployment. Engineered a hybrid backend using Java Spring Boot for secure authentication (BCrypt) and history management, integrated with a Python-based ML server via RESTful APIs. Implemented automated data profiling to dynamically detect task types (Classification/Regression) and generate real-time statistical insights. Developed a visualization engine to generate analytical plots including Confusion Matrix, Feature Importance, K-Means Clustering, and PCA projections.