MARC details
000 -LEADER |
fixed length control field |
02714nam a22002895i 4500 |
001 - CONTROL NUMBER |
control field |
36655 |
003 - CONTROL NUMBER IDENTIFIER |
control field |
0000000000 |
005 - DATE AND TIME OF LATEST TRANSACTION |
control field |
20240411192324.0 |
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
fixed length control field |
170522s2017 nyu s 000 0 eng |
010 ## - LIBRARY OF CONGRESS CONTROL NUMBER |
LC control number |
2017943201 |
020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
International Standard Book Number |
9783319554433 |
035 ## - SYSTEM CONTROL NUMBER |
System control number |
19656144 |
040 ## - CATALOGING SOURCE |
Original cataloging agency |
DLC |
Language of cataloging |
eng |
Description conventions |
rda |
Transcribing agency |
DLC |
042 ## - AUTHENTICATION CODE |
Authentication code |
pcc |
100 1# - MAIN ENTRY--PERSONAL NAME |
Personal name |
Skiena, Steven S. |
245 04 - TITLE STATEMENT |
Title |
The data science design manual / |
Statement of responsibility, etc. |
Steven S. Skiena. |
263 ## - PROJECTED PUBLICATION DATE |
Projected publication date |
1706 |
264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE |
Place of production, publication, distribution, manufacture |
New York, NY : |
Name of producer, publisher, distributor, manufacturer |
Springer Berlin Heidelberg, |
Date of production, publication, distribution, manufacture, or copyright notice |
2017. |
300 ## - PHYSICAL DESCRIPTION |
Extent |
pages cm. |
336 ## - CONTENT TYPE |
Content type term |
text |
Source |
rdacontent |
337 ## - MEDIA TYPE |
Media type term |
computer |
Source |
rdamedia |
338 ## - CARRIER TYPE |
Carrier type term |
online resource |
Source |
rdacarrier |
500 ## - GENERAL NOTE |
General note |
This engaging and clearly written textbook/reference provides a must-have introduction to the rapidly emerging interdisciplinary field of data science. It focuses on the principles fundamental to becoming a good data scientist and the key skills needed to build systems for collecting, analyzing, and interpreting data. The Data Science Design Manual is a source of practical insights that highlights what really matters in analyzing data, and provides an intuitive understanding of how these core concepts can be used. The book does not emphasize any particular programming language or suite of data-analysis tools, focusing instead on high-level discussion of important design principles. This easy-to-read text ideally serves the needs of undergraduate and early graduate students embarking on an "Introduction to Data Science" course. It reveals how this discipline sits at the intersection of statistics, computer science, and machine learning, with a distinct heft and character of its own. Practitioners in these and related fields will find this book perfect for self-study as well. Additional learning tools: Contains "War Stories," offering perspectives on how data science applies in the real world Includes "Homework Problems," providing a wide range of exercises and projects for self-study Provides a complete set of lecture slides and online video lectures at www.data-manual.com Provides "Take-Home Lessons," emphasizing the big-picture concepts to learn from each chapter Recommends exciting "Kaggle Challenges" from the online platform Kaggle Highlights "False Starts," revealing the subtle reasons why certain approaches fail Offers examples taken from the data science television show "The Quant Shop" (www.quant-shop.com). |
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name entry element |
Mathematical statistics--Data processing. |
Source of heading or term |
sears |
856 ## - ELECTRONIC LOCATION AND ACCESS |
Uniform Resource Identifier |
<a href="https://drive.google.com/file/d/15RgHavBaL5pISGkyePYgTKqDkNsnOaSp/view?usp=sharing">https://drive.google.com/file/d/15RgHavBaL5pISGkyePYgTKqDkNsnOaSp/view?usp=sharing</a> |