AI and Machine Learning graduate with hands-on experience developing intelligent applications using Python, Machine Learning, Deep Learning, and Computer Vision. Built an end-to-end YOLOv8-based Helmet Violation Detectio…
AI and Machine Learning graduate with hands-on experience developing intelligent applications using Python, Machine Learning, Deep Learning, and Computer Vision. Built an end-to-end YOLOv8-based Helmet Violation Detection System. Proficient in Python, TensorFlow, PyTorch, Scikit-learn, OpenCV, FastAPI, SQL, Pandas, and NumPy, with experience in data preprocessing, EDA, model development, evaluation, and deployment. Familiar with Transformers, Hugging Face, and LLM concepts.
<p>Gained hands-on experience in Python, Machine Learning, Deep Learning, and Data Science.<br>
Performed data preprocessing, EDA, feature engineering, and data visualization using Pandas, NumPy, and Matplotlib.<br>
Developed and evaluated ML models using Scikit-learn and TensorFlow.<br>
Worked with SQL databases, deployed ML models using Django, and gained foundational knowledge of Transformers, Hugging Face, and LLM concepts.</p>
<p>Developed an AI-based vehicle monitoring system that detects helmet violations using YOLO, identifies vehicle number plates, extracts plate numbers using OCR, retrieves vehicle owner details from a database, and automatically sends violation alerts through email. The system is integrated with a FastAPI backend and a web-based interface for officers to upload images and view detection results and alerts.</p><p>Python – Core development</p><p>YOLOv8 – Helmet and number plate detection</p><p>PaddleOCR / EasyOCR – Number plate text recognition</p><p>OpenCV – Image processing</p><p>FastAPI – Backend REST API</p><p>HTML, CSS, JavaScript – Web interface</p><p>SQLite – Vehicle, owner, and alert data storage</p><p>SMTP / Gmail – Automated email alerts</p><p>Ultralytics – YOLO model training and inference</p><p>Roboflow – Dataset preparation and annotation</p>
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