Explore advanced techniques for sketching high-dimensional data in this comprehensive lecture by Jelani Nelson from UC Berkeley. Delve into the intersection of probability, geometry, and computation as applied to high-dimensional spaces. Learn about cutting-edge methods for data compression and dimensionality reduction, essential for managing and analyzing large-scale datasets. Gain insights into the theoretical foundations and practical applications of sketching algorithms, their impact on machine learning, and their role in solving complex computational problems in high-dimensional settings.