At Full Stack Academy, I built 6+ end-to-end AI and ML projects, including RAG-based document Q&A systems, predictive analytics models, and CNN-based plant disease detection. My work improved model effectiveness by up to 30% and reduced manual analysis effort by 50+ hours per week through automation and intelligent workflows.
On my AI Doctor Assistant project, I developed an offline healthcare assistant that processes medical reports, ECGs, X-rays, and scanned documents using LLMs and multimodal AI. The project uses local processing to support privacy.
I also developed a medical image copyright protection system using Deep CNN feature extraction and zero-watermarking, and a plant disease detection system that reduced manual crop inspection effort by 20–25%. I work with Python, TensorFlow, PyTorch, and tools for building LLM applications and RAG pipelines.
