Statistics, Data Mining, and Machine Learning in Astronomy: A Practical Python Guide for the Analysis of Survey Data, Updated Edition (Princeton Series in Modern Observational Astronomy)
by Željko Ivezić, Andrew J. Connolly, Jacob T. Vanderplas, Alexander Gray
This updated practical guide introduces statistical analysis, data mining, and machine learning for astronomical survey data. Using Python, it supports readers exploring computational techniques relevant to modern observational astronomy and provides a foundation for analyzing the large datasets produced by contemporary surveys.
About This Book
This updated edition presents practical methods for analyzing astronomical survey data.
It focuses on the use of statistics, data mining, and machine learning in astronomy.
Python serves as the guide’s computational language for implementing and exploring analytical techniques.
Written for readers working with modern observational astronomy, the book connects computational practice with the study of survey data.
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