With the ever increasing amounts of data in electronic form, the need for automated methods
for data analysis continues to grow. The goal of machine learning is to develop methods that
can automatically detect patterns in data, and then to use the uncovered patterns to predict
future data or other outcomes of interest. Machine learning is thus closely related to the fields
of statistics and data mining, but differs slightly in terms of its emphasis and terminology. This
book provides a detailed introduction to the field, and includes worked examples drawn from
application domains such as molecular biology, text processing, computer vision, and robotics.
1