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I am a research-driven AI professional with a Master’s in Artificial Intelligence and over two years of hands-on experience working with data curation, annotation, and model training for computer vision and IoT projects. My background includes building and training computer vision models on curated datasets, performing exploratory data analysis, and implementing segmentation techniques such as K-Means Clustering. I am skilled in Python (Pandas, Numpy, Sklearn, Matplotlib), AWS (Glue, Athena, S3, SageMaker), and visualization tools like Tableau and Streamlit. My work has involved optimizing data pipelines, preparing high-quality datasets, and evaluating model performance on both pre-trained and custom models, especially for applications involving sensors and edge devices. I am passionate about ensuring data quality and integrity to support robust AI solutions.