Data science in higher education / (Record no. 16046)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 01471nam a2200229Ia 4500 |
| 003 - CONTROL NUMBER IDENTIFIER | |
| control field | NULRC |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20250520102820.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 250520s9999 xx 000 0 und d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 9781515206460 |
| 040 ## - CATALOGING SOURCE | |
| Transcribing agency | NULRC |
| 050 ## - LIBRARY OF CONGRESS CALL NUMBER | |
| Classification number | Q 181 .L39 2015 |
| 100 ## - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Lawson, Jesse |
| Relator term | author |
| 245 #0 - TITLE STATEMENT | |
| Title | Data science in higher education / |
| Statement of responsibility, etc. | Jesse Lawson |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. | |
| Place of publication, distribution, etc. | Chico, CA : |
| Name of publisher, distributor, etc. | Jesse Lawson, |
| Date of publication, distribution, etc. | c2015 |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | 213 pages ; |
| Dimensions | 23 cm. |
| 365 ## - TRADE PRICE | |
| Price amount | USD50.86 |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE | |
| Bibliography, etc. note | Includes bibliographical references. |
| 505 ## - FORMATTED CONTENTS NOTE | |
| Formatted contents note | What is data science? -- The data science cycle -- What is machine learning? -- Predicting numerical values with regression -- Predicting class membership with classification -- Naive Bayes Classification -- The road ahead (and looking back). |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc. | Data science in higher education is the process of turning raw institutional data into actionable intelligence. With this introduction to foundational topics in machine learning and predictive analytics, ambitious leaders in research can develop and employ sophisticated predictive models to better inform their institution's decision-making process. You don't need an advanced degree in math or statistics to do data science. With the open-source statistical programming language R, you'll learn how to tackle real-life institutional data challenges (with actual institutional data!) by going step-by-step through different case studies |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | DATA MINING |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Source of classification or shelving scheme | Library of Congress Classification |
| Koha item type | Books |
| Withdrawn status | Lost status | Source of classification or shelving scheme | Damaged status | Not for loan | Collection | Home library | Current library | Shelving location | Date acquired | Source of acquisition | Total checkouts | Full call number | Barcode | Date last seen | Copy number | Price effective from | Koha item type |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Library of Congress Classification | Gen. Ed. - CCIT | LRC - Graduate Studies | National University - Manila | General Circulation | 06/14/2017 | Purchased - Amazon | GC Q 181 .L39 2015 | NULIB000013805 | 05/20/2025 | c.1 | 05/20/2025 | Books |