MARC details
000 -LEADER |
fixed length control field |
03114nam a22005295i 4500 |
001 - CONTROL NUMBER |
control field |
ssj0002239821 |
003 - CONTROL NUMBER IDENTIFIER |
control field |
WaSeSS |
005 - DATE AND TIME OF LATEST TRANSACTION |
control field |
20250110114257.0 |
006 - FIXED-LENGTH DATA ELEMENTS--ADDITIONAL MATERIAL CHARACTERISTICS |
fixed length control field |
m d |
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION |
fixed length control field |
cr n |
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
fixed length control field |
190906s2019 xxu| o |||| 0|eng d |
020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
International Standard Book Number |
9781484249604 |
024 7# - OTHER STANDARD IDENTIFIER |
Standard number or code |
10.1007/978-1-4842-4961-1 |
Source of number or code |
doi |
040 ## - CATALOGING SOURCE |
Modifying agency |
WaSeSS |
Transcribing agency |
AIMIT LIBRARY |
050 #4 - LIBRARY OF CONGRESS CALL NUMBER |
Classification number |
QA76.73.P98 |
072 #7 - SUBJECT CATEGORY CODE |
Subject category code |
UMX |
Source |
bicssc |
072 #7 - SUBJECT CATEGORY CODE |
Subject category code |
COM051360 |
Source |
bisacsh |
072 #7 - SUBJECT CATEGORY CODE |
Subject category code |
UMX |
Source |
thema |
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER |
Classification number |
005.76821 |
Edition number |
1 |
Item number |
SINP |
092 ## - LOCALLY ASSIGNED DEWEY CALL NUMBER (OCLC) |
Classification number |
EBOOK |
999 ## - SYSTEM CONTROL NUMBERS (KOHA) |
Koha Dewey Subclass [OBSOLETE] |
03654381 |
100 1# - MAIN ENTRY--PERSONAL NAME |
Personal name |
Singh, Pramod. |
9 (RLIN) |
32236 |
245 10 - TITLE STATEMENT |
Title |
Learn PySpark: |
Remainder of title |
build python-based machine learning and deep learning models / |
Statement of responsibility, etc. |
By Pramod Singh. |
250 ## - EDITION STATEMENT |
Edition statement |
1st ed. |
260 ## - PUBLICATION, DISTRIBUTION, ETC. |
Place of publication, distribution, etc. |
New York : |
Name of publisher, distributor, etc. |
Apress , |
Date of publication, distribution, etc. |
2019. |
300 ## - PHYSICAL DESCRIPTION |
Extent |
xviii,210p. ; |
Dimensions |
23 cm. |
347 ## - DIGITAL FILE CHARACTERISTICS |
File type |
text file |
Encoding format |
PDF |
Source |
rda |
505 0# - FORMATTED CONTENTS NOTE |
Formatted contents note |
Chapter 1: Introduction to PySpark -- Chapter 2: Data Processing -- Chapter 3: Spark Structured Streaming -- Chapter 4: Airflow -- Chapter 5: Machine Learning Library (MLlib) -- Chapter 6: Supervised Machine Learning -- Chapter 7: Unsupervised Machine Learning -- Chapter 8: Deep Learning Using PySpark. |
506 ## - RESTRICTIONS ON ACCESS NOTE |
Terms governing access |
Requires an SPL library card. |
520 ## - SUMMARY, ETC. |
Summary, etc. |
Leverage machine and deep learning models to build applications on real-time data using PySpark. This book is perfect for those who want to learn to use this language to perform exploratory data analysis and solve an array of business challenges. You'll start by reviewing PySpark fundamentals, such as Spark's core architecture, and see how to use PySpark for big data processing like data ingestion, cleaning, and transformations techniques. This is followed by building workflows for analyzing streaming data using PySpark and a comparison of various streaming platforms. You'll then see how to schedule different spark jobs using Airflow with PySpark and book examine tuning machine and deep learning models for real-time predictions. This book concludes with a discussion on graph frames and performing network analysis using graph algorithms in PySpark. All the code presented in the book will be available in Python scripts on Github. |
538 ## - SYSTEM DETAILS NOTE |
System details note |
Mode of access: World Wide Web. |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name entry element |
Python (Computer program language) |
9 (RLIN) |
32237 |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name entry element |
Big data |
9 (RLIN) |
32238 |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name entry element |
Machine learning |
9 (RLIN) |
32239 |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name entry element |
Open source software |
9 (RLIN) |
32240 |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name entry element |
Computer programming |
9 (RLIN) |
32241 |
655 #7 - INDEX TERM--GENRE/FORM |
Genre/form data or focus term |
Electronic books. |
Source of term |
local |
9 (RLIN) |
32242 |
710 2# - ADDED ENTRY--CORPORATE NAME |
Corporate name or jurisdiction name as entry element |
SpringerLink (Online service) |
9 (RLIN) |
32243 |
710 2# - ADDED ENTRY--CORPORATE NAME |
Corporate name or jurisdiction name as entry element |
O'Reilly (Firm) |
9 (RLIN) |
32244 |
710 20 - ADDED ENTRY--CORPORATE NAME |
Corporate name or jurisdiction name as entry element |
Serials Solutions |
9 (RLIN) |
32245 |
773 0# - HOST ITEM ENTRY |
Title |
Springer eBooks |
776 08 - ADDITIONAL PHYSICAL FORM ENTRY |
Relationship information |
Printed edition: |
International Standard Book Number |
9781484249604 |
776 08 - ADDITIONAL PHYSICAL FORM ENTRY |
Relationship information |
Printed edition: |
International Standard Book Number |
9781484249628 |
856 40 - ELECTRONIC LOCATION AND ACCESS |
Link text |
View this electronic item in O'Reilly Online Learning: Academic/Public Library Edition. |
Uniform Resource Identifier |
<a href="https://ezproxy.spl.org/login?url=https://learning.oreilly.com/library/view/~/9781484249611/?ar">https://ezproxy.spl.org/login?url=https://learning.oreilly.com/library/view/~/9781484249611/?ar</a> |
Public note |
An e-book available through full-text database. |
942 ## - ADDED ENTRY ELEMENTS (KOHA) |
Source of classification or shelving scheme |
Dewey Decimal Classification |
Koha item type |
Book |
Edition |
1st |
Call number prefix |
005.76821 SINP |