CHIPPY RAVINDRAN E

Proficient in Python, TensorFlow, scikit-learn, pandas, numpy, matplotlib, OpenCV, Docker, AWS, and deep learning concepts, particularly CNNs. Developed a robust renal image segmentation model using TensorFlow and CNNs, including preprocessing data for enhanced performance and fine-tuning pre-trained architectures to achieve state-of-the-art results. Collaborated with medical experts to validate the model's accuracy and applicability in clinical settings. Experience in prostate cancer classification using machine learning algorithms and medical imaging data for disease diagnosis and risk assessment. Implemented deep learning techniques for accurate segmentation of C2 and L5 vertebrae, showcasing proficiency in medical image analysis. Developed a CNN model for whole-body tumor detection and multi-class classification model for breast cancer types. Demonstrated dedication to leveraging advanced technology for solving complex problems in healthcare and contributing innovative solutions to the field.

Contributed to projects using Django, SQL, and Python during internship. Delivered efficient solutions and contributed to team success.