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Practical Statistics for Data Scientists: 50+ Essential Concepts Using R and Python
Published by O'Reilly Media (edition 2), 2020
ISBN 10: 149207294X ISBN 13: 9781492072942
Language: English
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Practical Statistics for Data Scientists: 50+ Essential Concepts Using R and Python
Published by O'Reilly Media (edition 2), 2020
ISBN 10: 149207294X ISBN 13: 9781492072942
Language: English
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Practical Statistics for Data Scientists : 50+ Essential Concepts Using R and Python
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Practical Statistics for Data Scientists : 50+ Essential Concepts Using R and Python
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Practical Statistics for Data Scientists (Paperback)
Published by O'Reilly Media, Sebastopol, 2020
ISBN 10: 149207294X ISBN 13: 9781492072942
Language: English
Paperback. Condition: new. Paperback. 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 science How random sampling can reduce bias and yield a higher-quality dataset, even with big data How the principles of experimental design yield definitive answers to questions How to use regression to estimate outcomes and detect anomalies Key classification techniques for predicting which categories a record belongs to Statistical machine learning methods that ""learn"" from data Unsupervised learning methods for extracting meaning from unlabeled data" 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 whats important and whats not Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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Practical Statistics for Data Scientists : 50+ Essential Concepts Using R and Python
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Practical Statistics for Data Scientists: 50+ Essential Concepts Using R and Python
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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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Add to basketCondition: Good. [ No Hassle 30 Day Returns ][ Ships Daily ] [ Underlining/Highlighting: NONE ] [ Writing: NONE ] [ Edition: first ] Publisher: O'Reilly Media Pub Date: 2/25/2017 Binding: Paperback Pages: 250 first edition.
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Practical Statistics for Data Scientists: 50+ Essential Concepts Using R and Python
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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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Practical Statistics for Data Scientists : 50+ Essential Concepts Using R and Python
Published by O'reilly Media Jun 2020, 2020
ISBN 10: 149207294X ISBN 13: 9781492072942
Language: English
£ 61
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Add to basketTaschenbuch. Condition: Neu. Neuware - 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 practical guide-now including examples in Python as well as R-explains how to apply various 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 scientists use statistical methods but lack a deeper statistical perspective. If you're familiar with the R or Python programming languages, and have had some exposure to statistics but want to learn more, this quick reference bridges the gap in an accessible, readable format. With this updated edition, you'll dive into: Exploratory data analysis Data and sampling distributions Statistical experiments and significance testing Regression and prediction Classification Statistical machine learning Unsupervised learning.
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Add to basketpaperback. Condition: Good. 2nd Edition. Ships in a BOX from Central Missouri! May not include working access code. Will not include dust jacket. Has used sticker(s) and some writing or highlighting. UPS shipping for most packages, (Priority Mail for AK/HI/APO/PO Boxes).
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Practical Statistics for Data Scientists: 50+ Essential Concepts Using R and Python
Published by Oreilly & Associates Inc, 2020
ISBN 10: 149207294X ISBN 13: 9781492072942
Language: English
Paperback. Condition: Brand New. 2nd edition. 342 pages. 9.00x7.00x0.75 inches. In Stock.
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Add to basketCondition: New. 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 .
