Statistical Learning Theory | ETH Zurich | Joachim M. Buhmann

Comprehensive course on the fundamental principles and techniques of statistical learning theory, taught by renowned expert Joachim M. Buhmann at ETH Zurich.

Introduction

This course covers the fundamental principles and techniques of statistical learning theory, which provides a solid theoretical foundation for machine learning. It is taught by Professor Joachim M. Buhmann at ETH Zurich.

Highlights

• Comprehensive coverage of statistical learning theory, including topics such as empirical risk minimization, generalization bounds, and model selection
• Taught by a renowned expert in the field, Professor Joachim M. Buhmann
• Video lectures available on YouTube, making the course accessible to a wide audience

Recommendation

This course is highly recommended for anyone interested in gaining a deep understanding of the theoretical underpinnings of machine learning. It is particularly suitable for graduate students, researchers, and professionals working in the field of artificial intelligence and data science.

YouTube Videos