J. V. Wall is Adjunct Professor in the Department of Physics and Astronomy, University of British Columbia and Visiting Professor at the University of Oxford.
C. R. Jenkins is a Research Scientist in Earth Sciences and Resource Engineering at the Commonwealth Scientific and Industrial Research Organisation (CSIRO), Australia.
Statistics, Data Mining, and Machine Learning in Astronomy presents a wealth of practical analysis problems, evaluates techniques for solving them, and explains how to use various approaches for different types and sizes of data sets. For all applications described in the book, Python code and example data sets are provided. The supporting data sets have been carefully selected from contemporary astronomical surveys (for example, the Sloan Digital Sky Survey) and are easy to download and use. The accompanying Python code is publicly available, well documented, and follows uniform coding standards. Together, the data sets and code enable readers to reproduce all the figures and examples, evaluate the methods, and adapt them to their own fields of interest.