// what i've built
A collection of AI systems, open-source tools, and production deployments.
Automatically manage your university inbox with an AI that reads student questions, matches them to your approved guidelines, and sends out friendly, consistent replies 24/7 so no one is left waiting.
An Explainable AI (XAI) tool that identifies 20 types of Bengali market fishes, using visual heatmaps to show exactly how the AI makes its predictions.
A multi-label classification tool designed to categorize keywords from research abstracts, by an optimized BERT model and deployed through Flask.
An AI-powered artwork caption generator that uses a Swin Transformer and GPT-2 to automatically write creative titles for a digital art.
An Explainable AI tool detecting Oral Squamous Cell Carcinoma from medical images, using deep learning models like VGG-16 & LIME methods.
A complete data workflow that scrapes book data with Selenium, performs EDA with Pandas, and presents findings in a Tableau dashboard.
Detect bone fractures and identify body regions using CNN models on the MURA dataset, featuring Grad-CAM and XAI for transparent decision-making.
A Flutter mobile app detecting cancerous cells using a TensorFlow Lite model. Capture real-time images or upload from your gallery for instant diagnostics.
A Flutter e-commerce app transforming static UI into functional code, with Firebase API integration underway for real-time data.
A seamless bank app UI built using Flutter and Dart from Freepik designs. Includes functional frontend navigation and planned REST API backend systems.
Predict mobile phone prices based on hardware specifications! This ML project evaluates Ridge, Random Forest, and Gradient Boosting regressors.