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machine Learning Intern
CIIRC• August 2022 - February 2023
• Developed a Machine Learning model for categorizing and assessing cancerous cells in cases of breast cancer. • Utilized Machine Learning, Deep Learning, Explainable AI, Python and its libraries to enhance the performance of the model. • Conducted experiments to validate the model and achieved an accuracy of 94%. • Collaborated with a team of oncologists and a pathologist to develop a user-friendly interface for the model. • Contributed to the development of a research paper on "Comparative study of conventional ml/dl algorithms with explainable AI technique using annotated breast cancer biopsy images".
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