Machine Learning has become a key enabling technology for many
engineering applications, investigating scientific questions and
theoretical problems alike. To stimulate discussions and to
disseminate new results, a summer school series was started in
February 2002, the documentation of which is published as LNAI
2600.
This book presents revised lectures of two subsequent summer
schools held in 2003 in Canberra, Australia, and in T bingen,
Germany. The tutorial lectures included are devoted to statistical
learning theory, unsupervised learning, Bayesian inference, and
applications in pattern recognition; they provide in-depth
overviews of exciting new developments and contain a large number
of references.
Graduate students, lecturers, researchers and professionals
alike will find this book a useful resource in learning and
teaching machine learning.
General
Is the information for this product incomplete, wrong or inappropriate?
Let us know about it.
Does this product have an incorrect or missing image?
Send us a new image.
Is this product missing categories?
Add more categories.
Review This Product
No reviews yet - be the first to create one!