Computer Engineering student building real-world AI/ML applications across Computer Vision and NLP, including emotion recognition, RAG-based Q&A chatbots, and personalized recommendation systems.
Computer Engineering graduate with a strong interest in Artificial Intelligence and Machine Learning, backed by hands on experience building practical AI applications. Developed intelligent solutions including a real time emotion recognition system, a pet recommendation system, and an agricultural chatbot that answers questions from uploaded PDF documents using RAG and semantic search. Proficient in Python, FastAPI, TensorFlow, Scikit-learn, React, and TypeScript, with experience integrating OpenAI and Ollama models into AI applications. Passionate about solving real world problems through AI and eager to contribute as an AI/ML Engineer by building reliable, scalable, and impactful solutions.
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Tools
Developed a RAG-based AI chatbot for agricultural question answering. Implemented document upload, text extraction, chunking, FAISS-based semantic retrieval, and LLM-powered response generation to deliver accurate, context-aware answers from user-provided documents.
Tech Stack: Python, FastAPI, FAISS, Sentence Transformers, Ollama, PyMuPDF/PyPDF2
GitHub Demo
