R for Everyone by Lander
For sale is R for Everyone by Lander ISBN 9780134546926 013454692X.
Data Mesh: Delivering Data-Driven Value at Scale – Paperback – O’Reilly 2022
Excellent condition pre-owned copy with no writing, marking, damage, distress, or identifiable defects. Will be packaged and shipped carefully same or next day by an experienced seller.
The R Book,
Barely handled, with minimal wear. An outstanding copy, close to enjoy! You are purchasing a Like New copy of 'The R Book,'.
C. H. DAGLI – Intelligent Engineering Systems Neural Networks Vol 5 | NEW
A nice touch in this textbook is the list of key people and their contributions.
Professional C++ (Tech Today) – Paperback, by Gregoire Marc – Good
Professional C++ (Tech Today)by Gregoire, Marc Description: It's a preowned item in good condition and includes all the pages. It may have some general signs of wear and tear, such as markings, highlighting, slight damage to the cover, minimal wear to the binding, etc., but they will not affect the overall reading experience.Product ID: 1394193173-11-1
CompTIA A+ Guide to IT Technical Support (MindTap Course List) by Andrews, Jean
CompTIA A+ Guide to IT Technical Support (MindTap Course List). Title : CompTIA A+ Guide to IT Technical Support (MindTap Course List). Authors : Andrews, Jean. May not include working access code. Will not include dust jacket.
Introduction to Algorithms Hardcover BRAND NEW Fourth edition Cormen
Brand new copies of Algorithms, 4th Edition. Shipped in bubble wrap and a new mailer. 11 available at this price…buy one or multiples.
An Introduction to Statistical Learning: With Applications in R by James VG COND
"An Introduction to Statistical Learning: With Applications in R" is a comprehensive textbook by authors Trevor Hastie, Gareth James, Robert Tibshirani, and Daniela Witten. Published by Springer New York in 2017, this hardcover book covers a range of topics in mathematics and statistics, including machine learning and data analysis. With 426 pages and in English, this textbook is a valuable resource for students and professionals in the field of statistical learning. The book also includes practical applications in R, making it a practical and informative tool for those looking to deepen their understanding of statistical methods.
Springer Texts in Statistics Ser.: Introduction to Statistical Learning :…
Introduction to Statistical Learning: With Applications in R is a comprehensive textbook exploring topics in computers, mathematics, and statistical software. Published by Springer New York in 2017, this book offers a detailed introduction to statistical learning methods with a focus on R programming. Written by authors Trevor Hastie, Gareth James, Robert Tibshirani, and Daniela Witten, this hardcover textbook is a valuable resource for students and professionals interested in mathematical and statistical software, probability and statistics, and artificial intelligence and semantics. With 426 pages and a series of informative examples and exercises, this textbook provides a thorough introduction to the field of statistical learning.
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