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Introduction Statistical Learning Applications (124 results)
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Condition: Very Good. Used book that is in excellent condition. May show signs of wear or have minor defects.
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An Introduction to Statistical Learning: with Applications in R (Springer Texts in Statistics)
Published by Springer (edition Second Edition 2021), 2021
ISBN 10: 1071614177 ISBN 13: 9781071614174
Language: English
Hardcover. Condition: Good. Second Edition 2021. Ship within 24hrs. Satisfaction 100% guaranteed. APO/FPO addresses supported.
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An Introduction to Statistical Learning: with Applications in Python (Springer Texts in Statistics)
Published by Springer (edition 2023), 2023
ISBN 10: 3031387465 ISBN 13: 9783031387463
Language: English
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Tree-Based Methods for Statistical Learning in R: A Practical Introduction with Applications in R (Chapman & Hall/CRC Data Science Series)
Published by Chapman and Hall/CRC, 2022
ISBN 10: 0367532468 ISBN 13: 9780367532468
Language: English
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An Introduction to Statistical Learning: with Applications in R (Springer Texts in Statistics)
Published by Springer
hardcover. Condition: VeryGood. A copy that may have been read, very minimal wear and tear. May have a remainder mark.
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An Introduction to Statistical Learning: with Applications in R (Springer Texts in Statistics)
Published by Springer
hardcover. Condition: LikeNew. Used Like New, no missing pages, no damage to binding, may have a remainder mark.
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Add to basketN.A. Condition: New. ISBN:9781071614204.
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An Introduction to Statistical Learning with Applications in Python
Published by (Springer, Switzerland, 2023), 2023
Seller: Alcuin Books, ABAA/ILAB, Scottsdale, AZ, U.S.A.
Seller rating 5 out of 5 stars
First Edition
First Edition. Large Octavo. 607 pages Written by four experts of the field, this book offers an excellent entry to statistical learning to a broad audience, including those without strong background in mathematics. The focus is on explanation of concepts, description of methods, application of software,and interpretation of results. A reader only needs to know the basic concepts from an algebra-based elementary probability course, such as random variables, probability distribution, expectation, variance, conditional probability, and the Bayes theory. A fine copy bound in yellowpurple, red, blue and green paper covered boards lettered in yellow, white, and black.
