Explore topological data analysis and its application to biological image classification in this 30-minute conference talk. Learn how persistent homology, local homology, and average persistence landscapes can be combined with machine learning techniques to analyze high-resolution images of a cell's actin cytoskeleton. Discover a general approach that can be applied to various image classes, covering topics such as data science, persistence landscapes, stability, and support vector regression. Gain insights into the challenges and potential of this innovative method for analyzing biological structures through visualization techniques and real-world examples.