About
Entry-level AI/ML Engineer with hands-on experience in computer vision, deep learning, and machine learning model development. Skilled in Python, PyTorch, TensorFlow, YOLO, and Streamlit, with project experience in model training, evaluation, optimization, and deployment.
Education
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2025
QualificationIIT-M GUVI PravartakArtificial Intelligence and Machine Learning Program · Dec 2024 – May 2025
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2024
B.E.Thamirabharani Engineering collegeElectronics and Communication Engineering · Jun 2020 – Apr 2024
Skills
Tools / apps / platforms
Projects
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PowerPulse-Household-Energy-Usage-ForecastScikit-learn, Machine Learning, Feature Engineering, Data Visualization
Developed predictive models including Linear Regression, Random Forest, and Gradient Boosting to forecast household electricity consumption. Implemented feature engineering, outlier handling, and data preprocessing to improve forecasting accuracy and model stability.
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Multiclass-Fish-Image-Classification-deep-learningPython, PyTorch, CNNs, Transfer Learning, Streamlit
Built a multiclass image classification pipeline to identify 11 fish species using CNNs and pretrained architectures. Applied transfer learning with MobileNetV2 and deployed a Streamlit web application for real-time prediction with confidence scores.
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Military-Soldier-Safety-and-Weapon-Detection-using-YOLO-and-Computer-VisionPython, YOLOv8, OpenCV, Deep Learning, Streamlit
Designed and developed a real-time multi-class object detection system to identify soldiers, weapons, vehicles, civilians, and trenches for battlefield threat awareness. Fine-tuned YOLOv8m using transfer learning on a custom-annotated dataset and deployed the model using Streamlit for image/video uploads and real-time inference.