A showcase of innovative solutions, from AI-powered applications to full-stack platforms.
Developing a full-stack school management platform using Next.js, Prisma ORM, and MySQL for seamless data management. Implementing authentication, attendance tracking, grade management, and fee monitoring modules with responsive UI and API-driven backend.
Built a multi-role Flask web application for daily staff reporting, task tracking, and performance analysis. Integrated AWS RDS for secure and scalable cloud-based data storage with role-based dashboards (Admin, Academic, and MD) with analytics and automated summary reports.
Designed an intelligent forecasting model using time-series analysis and LSTM networks to predict future retail sales. Integrated external factors such as seasonality and promotions for improved forecasting accuracy. Deployed with a Flask API and interactive dashboard for visualization and decision support.
Created a RAG-based LLM system enabling users to upload PDF files, process their content, and retrieve context-aware answers via natural language queries. Built using LangChain, Chroma, and Ollama for embedding generation and conversational retrieval. Designed an interactive chat interface for real-time, document-driven AI assistance.
Developed a convolutional neural network (CNN)-based deep learning model for paddy leaf disease classification. Performed image preprocessing using augmentation, normalization, and segmentation to enhance model accuracy. Utilized transfer learning with EfficientNetB0 to achieve high precision in disease detection and classification. Implemented a visualization dashboard for model predictions and performance tracking.
Designed and developed a modern, responsive portfolio website showcasing professional projects, skills, and experience. Built with Next.js 15, TypeScript, and Tailwind CSS for optimal performance and SEO. Features include interactive 3D animated backgrounds, dynamic project showcases, contact form with email integration, responsive design across all devices, and optimized image loading.
Developed comprehensive data analytics solutions using SQL, Power BI, and Python for educational institutions and business clients. Created interactive dashboards that transform raw data into actionable insights through advanced data modeling, ETL workflows, and automated reporting.
Built a predictive machine learning model to identify at-risk customers with 95% accuracy. Utilized XGBoost and Scikit-Learn for classification, with a Streamlit dashboard for real-time inference and visualization of customer risk factors.
Developed a real-time sentiment analysis system using BERT and PyTorch to track brand sentiment on social media. Implemented a FastAPI backend to process text streams and a React frontend to visualize sentiment trends and key topics.
