MARC details
| 000 -LEADER |
|---|
| fixed length control field |
02937nam a22004575i 4500 |
| 003 - CONTROL NUMBER IDENTIFIER |
|---|
| control field |
DE-He213 |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
|---|
| control field |
20231104114437.0 |
| 007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION |
|---|
| fixed length control field |
cr nn 008mamaa |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
|---|
| fixed length control field |
150715s2015 gw | s |||| 0|eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
|---|
| International Standard Book Number |
9783319200101 |
| Canceled/invalid ISBN |
978-3-319-20010-1 |
| 024 7# - OTHER STANDARD IDENTIFIER |
|---|
| Standard number or code |
10.1007/978-3-319-20010-1 |
| Source of number or code |
doi |
| 040 ## - CATALOGING SOURCE |
|---|
| Original cataloging agency |
TR-AnTOB |
| Language of cataloging |
eng |
| Transcribing agency |
TR-AnTOB |
| Description conventions |
rda |
| 050 #4 - LIBRARY OF CONGRESS CALL NUMBER |
|---|
| Classification number |
Q334-342 |
| 072 #7 - SUBJECT CATEGORY CODE |
|---|
| Subject category code |
UYQ |
| Source |
bicssc |
|
|---|
| Subject category code |
COM004000 |
| Source |
bisacsh |
|
|---|
| Subject category code |
UYQ |
| Source |
thema006.3 |
| -- |
23 |
| 041 ## - LANGUAGE CODE |
|---|
| Language code of text/sound track or separate title |
İngilizce |
| 100 1# - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Kubat, Miroslav. |
| Relator term |
author. |
| Relator code |
aut |
| -- |
http://id.loc.gov/vocabulary/relators/aut |
| 245 13 - TITLE STATEMENT |
|---|
| Title |
An Introduction to Machine Learning / |
| Statement of responsibility, etc. |
by Miroslav Kubat. |
| 264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE |
|---|
| Place of production, publication, distribution, manufacture |
Cham : |
| Name of producer, publisher, distributor, manufacturer |
Springer International Publishing : |
| -- |
Imprint: Springer, |
| Date of production, publication, distribution, manufacture, or copyright notice |
2015. |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
1 online resource |
| 336 ## - CONTENT TYPE |
|---|
| Content type term |
text |
| Content type code |
txt |
| Source |
rdacontent |
| 337 ## - MEDIA TYPE |
|---|
| Media type term |
computer |
| Media type code |
c |
| Source |
rdamedia |
| 338 ## - CARRIER TYPE |
|---|
| Carrier type term |
online resource |
| Carrier type code |
cr |
| Source |
rdacarrier |
| 347 ## - DIGITAL FILE CHARACTERISTICS |
|---|
| File type |
text file |
| Encoding format |
PDF |
| Source |
rda |
| 505 0# - FORMATTED CONTENTS NOTE |
|---|
| Formatted contents note |
A Simple Machine-Learning Task -- Probabilities: Bayesian Classifiers -- Similarities: Nearest-Neighbor Classifiers -- Inter-Class Boundaries: Linear and Polynomial Classifiers -- Artificial Neural Networks -- Decision Trees -- Computational Learning Theory -- A Few Instructive Applications -- Induction of Voting Assemblies -- Some Practical Aspects to Know About -- Performance Evaluation.-Statistical Significance -- The Genetic Algorithm -- Reinforcement learning. |
| 520 ## - SUMMARY, ETC. |
|---|
| Summary, etc. |
This book presents basic ideas of machine learning in a way that is easy to understand, by providing hands-on practical advice, using simple examples, and motivating students with discussions of interesting applications. The main topics include Bayesian classifiers, nearest-neighbor classifiers, linear and polynomial classifiers, decision trees, neural networks, and support vector machines. Later chapters show how to combine these simple tools by way of “boosting,” how to exploit them in more complicated domains, and how to deal with diverse advanced practical issues. One chapter is dedicated to the popular genetic algorithms. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Artificial intelligence. |
|
|---|
| Topical term or geographic name entry element |
Computer simulation. |
|
|---|
| Topical term or geographic name entry element |
Information storage and retrieva. |
|
|---|
| Topical term or geographic name entry element |
Optical pattern recognition. |
|
|---|
| Topical term or geographic name entry element |
Artificial Intelligence. |
| Authority record control number or standard number |
http://scigraph.springernature.com/things/product-market-codes/I21000 |
|
|---|
| Topical term or geographic name entry element |
Simulation and Modeling. |
| Authority record control number or standard number |
http://scigraph.springernature.com/things/product-market-codes/I19000 |
|
|---|
| Topical term or geographic name entry element |
Information Storage and Retrieval. |
| Authority record control number or standard number |
http://scigraph.springernature.com/things/product-market-codes/I18032 |
|
|---|
| Topical term or geographic name entry element |
Pattern Recognition. |
| Authority record control number or standard number |
http://scigraph.springernature.com/things/product-market-codes/I2203X |
| 710 2# - ADDED ENTRY--CORPORATE NAME |
|---|
| Corporate name or jurisdiction name as entry element |
SpringerLink (Online service) |
| 856 40 - ELECTRONIC LOCATION AND ACCESS |
|---|
| Materials specified |
Springer eBooks |
| Public note |
Online access link to the resource |
| Uniform Resource Identifier |
<a href="https://doi.org/10.1007/978-3-319-20010-1">https://doi.org/10.1007/978-3-319-20010-1</a> |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Source of classification or shelving scheme |
Library of Congress Classification |
| Koha item type |
E-Book |
