AG 3: Teaching
Lecturer: Thomas Lengauer
Tutor: Jörg Rahnenführer
Course language: The course is taught in English
|Course:||Thursday 13-16, Building 46, Room 024; starting on Thursday, October 24, 2002.|
|Tutorial:||Wednesday 13.30-15, Building 45, Room 014; starting on Wednesday, October 30, 2002.|
Advanced students in math, computer science, science students
with substantial mathematical background
Prerequisites: Vordiplom in Math. or Computer Science or equivalent. Basic knowledge in statistics.
Hastie, Tibshirani, Friedman: The Elements of Statistical Learning, Springer 2001. The readers of the course are encouraged to acquire this book.
Statistical Learning is a fundamental methodology that is central to data mining. As such the method has many fields of application, including computational biology, vision and scene analysis, geographic databases, robotics etc. The aim of the course is to present an overview of statistical learning methods that enable the listeners to go into depth on specific topics of their choice. This means that we will not present all details of the chapters. Nevertheless, all chapters will be touched, in order to span the whole field within one semester, at least at some level. The course will be patterned after the introductory text mentioned above. Each lecture will cover one chapter of the book. Thus, the topics of the lectures will be:
50% of the homework, final exam (probably oral)