Suresh Amgoth

I am a dedicated professional transitioning from a background in biotechnology to the dynamic field of data science. My experience includes analyzing genomic and biological datasets, building machine learning models, and exploring genetic risk factors. I am proficient in data analysis and preprocessing using Python, and I have hands-on experience with deep learning frameworks like TensorFlow and data visualization tools such as Matplotlib and Seaborn.

Currently, I am working on my Master’s thesis at Justus Liebig University Giessen, where I am advancing phylogenetic tree visualization in the EDGAR platform. My role involves developing interactive visualizations and optimizing performance for browser-based genomic data tools. Additionally, I have contributed to the OpenGeoSys project, ensuring high validation success rates for simulation project files through automated XML validation tests.

My projects, such as the Potato Leaf Disease Classification using deep learning, showcase my ability to apply machine learning techniques effectively. I am committed to continuous learning and have completed several certifications, including the Google Data Analytics Professional Certificate and a Python for Data Science Bootcamp, which further enhance my skills in data science.