As an AI Engineer Intern at Elevvo, I assisted with end-to-end machine learning workflows, including data collection, preprocessing, and model training. I also performed exploratory data analysis and prepared clean datasets.
In my projects, I developed a YOLO-based real-time object detection system with monocular distance estimation and collision risk analysis. I built an interactive Gradio interface for video uploads and live camera inference.
I also created a diabetes prediction system using Random Forest and XGBoost, achieving approximately 90% model accuracy. For crop disease detection, I fine-tuned a pre-trained ResNet model and deployed it as a Streamlit application.
