In this mind-bending episode of Scraping Bits, host DeGatchi sits down with Professor Bastian Grossenbacher-Rieck to explore the fascinating intersection of topology and machine learning.

Key topics covered:

Introduction to topological machine learning and its applications
How topological data analysis can uncover hidden patterns in complex datasets
The mathematical foundations of persistent homology
Real-world use cases of topological methods in data science and AI
Challenges and future directions in this emerging field

Professor Grossenbacher-Rieck breaks down complex concepts into digestible explanations, making cutting-edge research accessible to listeners. Whether you're a data scientist, AI researcher, or just curious about advanced analytics, this episode offers valuable insights into how topology is reshaping our approach to machine learning and data analysis.Tune in for an intellectually stimulating discussion that will expand your understanding of the latest developments in data science and artificial intelligence. Don't miss this opportunity to learn from one of the leading experts in topological machine learning!

Follow Scraping Bits on Twitter: ⁠⁠https://x.com/scrapingbits⁠⁠
Your Host, DeGatchi: ⁠⁠https://x.com/DeGatchi⁠⁠
Guest Speaker: ⁠⁠https://x.com/⁠pseudomanifold

Please support this podcast by checking out our sponsors:

Keywords: mathematics, math, game theory, calculus, linear algebra, category theory, signal processing, statistics, probability, solo auditor, public auditing platforms, private audits, scalability, freedom, Scraping Bits podcast, blockchain technology, audit industry, flashbots, reverse engineering, cybersecurity, infosec, mev, mev bot, quant.

#114 - Bastian Grossenbacher-Rieck: Topological Machine Learning + Topological Data Analysis Professor

Scraping Bits