MARC details
| 000 -LEADER |
|---|
| fixed length control field |
03202cam a2200349 i 4500 |
| 003 - CONTROL NUMBER IDENTIFIER |
|---|
| control field |
OSt |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
|---|
| control field |
20240710105947.0 |
| 007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION |
|---|
| fixed length control field |
ta |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
|---|
| fixed length control field |
220502s2017 njuad 001 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
|---|
| International Standard Book Number |
9781119327639 |
| Qualifying information |
(paperback) |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
|---|
| International Standard Book Number |
1119327636 |
| Qualifying information |
(paperback) |
| 040 ## - CATALOGING SOURCE |
|---|
| Original cataloging agency |
TUPM |
| Language of cataloging |
eng |
| Description conventions |
rda |
| Transcribing agency |
TUPM |
| 050 #0 - LIBRARY OF CONGRESS CALL NUMBER |
|---|
| Classification number |
T 58.5 |
| Item number |
P54 2017 |
| 100 1# - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Pierson, Lillian, |
| Relator term |
author. |
| 245 00 - TITLE STATEMENT |
|---|
| Title |
Data science for dummies / |
| Statement of responsibility, etc. |
by Lillian Pierson ; foreword by Jake Porway. |
| 250 ## - EDITION STATEMENT |
|---|
| Edition statement |
2nd edition. |
| 264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE |
|---|
| Place of production, publication, distribution, manufacture |
Hoboken, NJ : |
| Name of producer, publisher, distributor, manufacturer |
John Wiley and Sons, Inc., |
| Date of production, publication, distribution, manufacture, or copyright notice |
[2017]. |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
xvi, 364 pages : |
| Other physical details |
illustrations, charts ; |
| Dimensions |
24 cm. |
| 336 ## - CONTENT TYPE |
|---|
| Content type term |
text |
| Source |
rdacontent |
| 336 ## - CONTENT TYPE |
|---|
| Content type term |
still image |
| Source |
rdacontent |
| 337 ## - MEDIA TYPE |
|---|
| Media type term |
unmediated |
| Source |
rdamedia |
| 338 ## - CARRIER TYPE |
|---|
| Carrier type term |
volume |
| Source |
rdacarrier |
| 500 ## - GENERAL NOTE |
|---|
| General note |
Includes index. |
| 505 0# - FORMATTED CONTENTS NOTE |
|---|
| Formatted contents note |
Getting Started With Data Science -- Wrapping Your Head around Data Science -- Exploring Data Engineering Pipelines and Infrastructure -- Applying Data-Driven Insights to Business and Industry -- Using Data Science to Extract Meaning from Your Data -- Machine Learning: Learning from Data with your Machine -- Math, Probability, and Statistical Modeling -- Using Clustering to Subdivide Data -- Modeling with Instances -- Building models that Operate Internet-of-Things Devices -- Creating Data Visualizations that Clearly Communicate Meaning -- Following the Principles of Data Visualization Design -- Using D3.js for Data Visualization -- Web-Based Applications for Visualization Design -- Exploring Best Practices in Dashboard Design -- Making Maps from Spatial Data -- Computing for Data Science -- Using Python for Data Science -- Using Open Source R for Data Science -- Using SQL in Data Science -- Doing Data Science with Excel and Knime -- Applying Domain Expertise to Solve Real-World Problems Using Data Science -- Data Science in Journalism: Nailing Down the Five Ws (and an H) -- Delving into Environmental Data Science -- Data Science for Driving Growth in E-Commerce -- Using Data Science to Describe and Predict Criminal Activity -- The Part of Tens --Ten Phenomenal Resources for Open Data -- Ten Free Data Science Tools and Applications. |
| 520 ## - SUMMARY, ETC. |
|---|
| Summary, etc. |
Begins by explaining large data sets and data formats, including sample Python code for manipulating data. The book explains how to work with relational databases and unstructured data, including NoSQL. The book then moves into preparing data for analysis by cleaning it up or "munging" it. From there the book explains data visualization techniques and types of data sets. Part II of the book is all about supervised machine learning, including regression techniques and model validation techniques. Part III explains unsupervised machine learning, including clustering and recommendation engines. Part IV overviews big data processing, including MapReduce, Hadoop, Dremel, Storm, and Spark. The book finishes up with real world applications of data science and how data science fits into organizations. |
| 650 10 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Information retrieval. |
| 650 10 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Data mining. |
| 650 10 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Information technology. |
| 650 10 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Databases. |
| 700 1# - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Porway, Jake, |
| Relator term |
writer of introductory text. |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Source of classification or shelving scheme |
Library of Congress Classification |
| Koha item type |
Book |