TDALabs - Some of TDA's Greatest Hits in Interactive Python

Explore the world of Topological Data Analysis (TDA) through an interactive Python tutorial showcasing some of the field's most significant applications. Dive into the scikit-tda library and the TDALabs repository, learning how to apply TDA techniques to various data types. Discover the stability theorem, analyze time series and video data using sliding windows, explore the natural space of image patches, and investigate diffusion maps in TDA. Gain hands-on experience with lower star image filtrations for cell segmentation, mesh reconstruction via alpha shapes, and isometry blind 3D shape clustering. Engage with practical examples that demonstrate TDA's versatility across multiple domains, including audio processing, video analysis, and machine learning on persistence diagrams. By the end of this tutorial, acquire the skills to leverage TDA in your own research or data science projects, and contribute to the growing field of topological data analysis.

Introduction
Basic Shapes
Vajratine
Sliding Window
Persistence
Audio
Video
Vocal folds
FFT preprocessing
Sample image
Sublevel filtrations
Mesh filtrations
Machine learning on persistence diagrams
Persistence images
Hyper parameters