Audio Data Collection
Collected and classified thousands of audio sounds for an academic deep learning project.
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I am a data scientist with a strong background in machine learning, deep learning, and natural language processing, with hands-on experience in data labeling, annotation, and curation for complex AI projects. My work includes leading research on deepfake detection in medical imagery and hate speech detection using custom datasets, where I managed the entire data lifecycle from collection and cleaning to annotation and evaluation. I am skilled in Python, SQL, TensorFlow, PyTorch, and NLP techniques such as tokenization and sentiment analysis, and have curated datasets for low-resource languages and online forums. My experience as a product tester and QA reviewer for AI tools has strengthened my attention to detail and quality assurance in data preparation, ensuring that training data meets high standards for model development.
Collected and classified thousands of audio sounds for an academic deep learning project.
Worked with a team to source and label diverse medical images. We also ensured data quality and patient privacy. We preprocessed the data to filter corrupt images and classified the images based on recommended classifications.
Master of Science, Data Science
Independent Researcher
Digital Content Manager & Data Analyst