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Published by O'Reilly Media, Incorporated, 2020
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Published by O'Reilly Media, O'Reilly Media, 2020
ISBN 10: 149207294X ISBN 13: 9781492072942
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Paperback. Condition: Fine. Practical Statistics for Data Scientists: 50+ Essential Concepts Using R and Python by Peter Bruce; Andrew Bruce; Peter Gedeck. O'Reilly Media, 2020. 360pp. Language: English. Note:
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Paperback. Condition: New. Statistical methods are a key part of data science, yet few data scientists have formal statistical training. Courses and books on basic statistics rarely cover the topic from a data science perspective. The second edition of this popular guide adds comprehensive examples in Python, provides practical guidance on applying statistical methods to data science, tells you how to avoid their misuse, and gives you advice on what's important and what's not.Many data science resources incorporate statistical methods but lack a deeper statistical perspective. If you're familiar with the R or Python programming languages and have some exposure to statistics, this quick reference bridges the gap in an accessible, readable format.With this book, you'll learn:Why exploratory data analysis is a key preliminary step in data scienceHow random sampling can reduce bias and yield a higher-quality dataset, even with big dataHow the principles of experimental design yield definitive answers to questionsHow to use regression to estimate outcomes and detect anomaliesKey classification techniques for predicting which categories a record belongs toStatistical machine learning methods that "learn" from dataUnsupervised learning methods for extracting meaning from unlabeled data.
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Add to basketPaperback. Condition: New. Statistical methods are a key part of data science, yet few data scientists have formal statistical training. Courses and books on basic statistics rarely cover the topic from a data science perspective. The second edition of this popular guide adds comprehensive examples in Python, provides practical guidance on applying statistical methods to data science, tells you how to avoid their misuse, and gives you advice on what's important and what's not.Many data science resources incorporate statistical methods but lack a deeper statistical perspective. If you're familiar with the R or Python programming languages and have some exposure to statistics, this quick reference bridges the gap in an accessible, readable format.With this book, you'll learn:Why exploratory data analysis is a key preliminary step in data scienceHow random sampling can reduce bias and yield a higher-quality dataset, even with big dataHow the principles of experimental design yield definitive answers to questionsHow to use regression to estimate outcomes and detect anomaliesKey classification techniques for predicting which categories a record belongs toStatistical machine learning methods that "learn" from dataUnsupervised learning methods for extracting meaning from unlabeled data.
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Gr.-8°(=22,5-25cm), Broschiert. Condition: Gut. Übersetzung der 2. Auflage. XV, 356 S., Ill. Praktische Statistik für Data Scientists. 50+ essenzielle Konzepte mit R und Python. [Practical statistics for data scientists] Deutsche Übersetzung von Marcus Fraaß. Einband leicht bestoßen. Sonst guter Gesamtzustand. Sprache: Deutsch Gewicht in Gramm: 680.
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hardcover. Condition: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority!
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Add to basketCondition: good. May show signs of wear, highlighting, writing, and previous use. This item may be a former library book with typical markings. No guarantee on products that contain supplements Your satisfaction is 100% guaranteed. Twenty-five year bookseller with shipments to over fifty million happy customers.