MARC details
| 000 -LEADER |
|---|
| fixed length control field |
03007cam a22003978i 4500 |
| 001 - CONTROL NUMBER |
|---|
| control field |
22930140 |
| 003 - CONTROL NUMBER IDENTIFIER |
|---|
| control field |
OSt |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
|---|
| control field |
20240103113426.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
|---|
| fixed length control field |
230114s2023 flu b 001 0 eng |
| 010 ## - LIBRARY OF CONGRESS CONTROL NUMBER |
|---|
| LC control number |
2022052592 |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
|---|
| International Standard Book Number |
9780815354475 (hardback) |
|
|---|
| International Standard Book Number |
9780815354390 (paperback) |
| 040 ## - CATALOGING SOURCE |
|---|
| Original cataloging agency |
DLC |
| Language of cataloging |
eng |
| Description conventions |
rda |
| Transcribing agency |
DLC |
| 042 ## - AUTHENTICATION CODE |
|---|
| Authentication code |
pcc |
| 082 00 - DEWEY DECIMAL CLASSIFICATION NUMBER |
|---|
| Classification number |
005.7 |
| 100 1# - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Lin, Hui |
| Titles and words associated with a name |
(Quantitative researcher), |
| Relator term |
author. |
| 245 10 - TITLE STATEMENT |
|---|
| Title |
Practitioner's guide to data science / |
| Statement of responsibility, etc. |
Hui Lin and Ming Li. |
| 250 ## - EDITION STATEMENT |
|---|
| Edition statement |
First edition. |
| 263 ## - PROJECTED PUBLICATION DATE |
|---|
| Projected publication date |
2304 |
| 264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE |
|---|
| Place of production, publication, distribution, manufacture |
Boca Raton : |
| Name of producer, publisher, distributor, manufacturer |
CRC Press, |
| Date of production, publication, distribution, manufacture, or copyright notice |
©2023. |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
xxiii, 378 pages : |
| Dimensions |
23 cm. |
| 336 ## - CONTENT TYPE |
|---|
| Content type term |
text |
| Content type code |
txt |
| Source |
rdacontent |
| 337 ## - MEDIA TYPE |
|---|
| Media type term |
unmediated |
| Media type code |
n |
| Source |
rdamedia |
| 338 ## - CARRIER TYPE |
|---|
| Carrier type term |
volume |
| Carrier type code |
nc |
| Source |
rdacarrier |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE |
|---|
| Bibliography, etc. note |
Includes bibliographical references and index. |
| 505 0# - FORMATTED CONTENTS NOTE |
|---|
| Formatted contents note |
Soft skills for data scientists -- Introduction to the data -- Big data cloud platform -- Data pre-processing -- Data wrangling -- Model tuning strategy -- Measuring performance -- Regression models -- Regularization methods -- Tree-based methods -- Deep learning. |
| 520 ## - SUMMARY, ETC. |
|---|
| Summary, etc. |
"This book aims to increase the visibility of data science in real-world, which differs from what you learn from a typical textbook. Many aspects of day-to-day data science work are almost absent from conventional statistics, machine learning, and data science curriculum. Yet these activities account for a considerable share of the time and effort for data professionals in the industry. Based on industry experience, this book outlines real-world scenarios and discusses pitfalls that data science practitioners should avoid. It also covers the big data cloud platform and the art of data science, such as soft skills. The authors use R as the primary tool and provide code for both R and Python. This book is for readers who want to explore possible career paths and eventually become data scientists. This book comprehensively introduces various data science fields, soft and programming skills in data science projects, and potential career paths. Traditional data-related practitioners such as statisticians, business analysts, and data analysts will find this book helpful in expanding their skills for future data science careers. Undergraduate and graduate students from analytics-related areas will find this book beneficial to learn real-world data science applications. Non-mathematical readers will appreciate the reproducibility of the companion R and python codes"-- |
| Assigning source |
Provided by publisher. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Big data. |
|
|---|
| Topical term or geographic name entry element |
Data mining. |
|
|---|
| Topical term or geographic name entry element |
Database management. |
| 700 1# - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Li, Ming |
| Titles and other words associated with a name |
(Research science manager), |
| Relator term |
author. |
| 776 08 - ADDITIONAL PHYSICAL FORM ENTRY |
|---|
| Relationship information |
Online version: |
| Main entry heading |
Lin, Hui (Quantitative researcher) |
| Title |
Practitioner's guide to data science. |
| Edition |
First edition |
| Place, publisher, and date of publication |
Boca Raton : CRC Press, 2023 |
| International Standard Book Number |
9781351132916 |
| Record control number |
(DLC) 2022052593 |
| 906 ## - LOCAL DATA ELEMENT F, LDF (RLIN) |
|---|
| a |
7 |
| b |
cbc |
| c |
orignew |
| d |
1 |
| e |
ecip |
| f |
20 |
| g |
y-gencatlg |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Source of classification or shelving scheme |
Dewey Decimal Classification |
| Koha item type |
Books |
| Suppress in OPAC |
No |
