دانلود کتاب Statistics, data mining, and machine learning in astronomy : a practical Python guide for the analysis of survey data – آمار ، داده کاوی و یادگیری ماشین در نجوم: یک راهنمای عملی پایتون برای تجزیه و تحلیل داده های نظرسنجی
سری Princeton series in modern observational astronomy
ویرایش Updated edition
سال 2020
نویسنده (گان) Alexander Gray, Jacob T VanderPlas, Andrew J. Connolly, eljko Ivezi─
ناشر Princeton University Press
زبان English
تعداد صفحات
حجم فایل 11.43MB
فرمت فایل epub
شابک 9780691197050, 0691197059
قیمت محصول :
45,000 تومان
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تمامی کتاب های موجود در وبسایت سای وان به زبان انگلیسی میباشد
‘As telescopes, detectors, and computers grow ever more powerful, the volume of data at the disposal of astronomers and astrophysicists will enter the petabyte domain, providing accurate measurements for billions of celestial objects. This book provides a comprehensive and accessible introduction to the cutting-edge statistical methods needed to efficiently analyze complex data sets from astronomical surveys such as the Panoramic Survey Telescope and Rapid Response System, the Dark Energy Survey, and the upcoming Large Synoptic Survey Telescope. It serves as a practical handbook for graduate students and advanced undergraduates in physics and astronomy, and as an indispensable reference for researchers. The updates in this new edition will include fixing ‘code rot,’ correcting errata, and adding some new sections. In particular, the new sections include new material on deep learning methods, hierarchical Bayes modeling, and approximate Bayesian computation. 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’–Read more…
Abstract: ‘As telescopes, detectors, and computers grow ever more powerful, the volume of data at the disposal of astronomers and astrophysicists will enter the petabyte domain, providing accurate measurements for billions of celestial objects. This book provides a comprehensive and accessible introduction to the cutting-edge statistical methods needed to efficiently analyze complex data sets from astronomical surveys such as the Panoramic Survey Telescope and Rapid Response System, the Dark Energy Survey, and the upcoming Large Synoptic Survey Telescope. It serves as a practical handbook for graduate students and advanced undergraduates in physics and astronomy, and as an indispensable reference for researchers. The updates in this new edition will include fixing ‘code rot,’ correcting errata, and adding some new sections. In particular, the new sections include new material on deep learning methods, hierarchical Bayes modeling, and approximate Bayesian computation. 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’
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ترجمه ماشینی :
“از آنجا که تلسکوپ ها ، ردیاب ها و رایانه ها قدرتمندتر می شوند ، حجم داده های موجود در اخترشناسان و اخترشناسان وارد دامنه پتابیت می شوند و اندازه گیری های دقیقی را برای میلیاردها اشیاء آسمانی فراهم می کنند. این کتاب مقدمه ای جامع و در دسترس را برای روشهای آماری برش مورد نیاز برای تجزیه و تحلیل کارآمد مجموعه داده های پیچیده از نظرسنجی های نجومی مانند