MARC details
| 000 -LEADER |
|---|
| fixed length control field |
03948cam a22005775i 4500 |
| 001 - CONTROL NUMBER |
|---|
| control field |
21772749 |
| 003 - CONTROL NUMBER IDENTIFIER |
|---|
| control field |
OSt |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
|---|
| control field |
20250426155915.0 |
| 006 - FIXED-LENGTH DATA ELEMENTS--ADDITIONAL MATERIAL CHARACTERISTICS |
|---|
| fixed length control field |
m |o d | |
| 007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION |
|---|
| fixed length control field |
cr ||||||||||| |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
|---|
| fixed length control field |
160316s2016 gw |||| o |||| 0|eng |
| 010 ## - LIBRARY OF CONGRESS CONTROL NUMBER |
|---|
| LC control number |
2019762086 |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
|---|
| International Standard Book Number |
9783319307176 |
| 024 7# - OTHER STANDARD IDENTIFIER |
|---|
| Standard number or code |
10.1007/978-3-319-30717-6 |
| Source of number or code |
doi |
| 035 ## - SYSTEM CONTROL NUMBER |
|---|
| System control number |
(DE-He213)978-3-319-30717-6 |
| 040 ## - CATALOGING SOURCE |
|---|
| Original cataloging agency |
DLC |
| Language of cataloging |
eng |
| Description conventions |
pn |
| -- |
rda |
| Transcribing agency |
JKRC |
| 072 #7 - SUBJECT CATEGORY CODE |
|---|
| Subject category code |
TEC041000 |
| Source |
bisacsh |
| 072 #7 - SUBJECT CATEGORY CODE |
|---|
| Subject category code |
TJK |
| Source |
bicssc |
| 072 #7 - SUBJECT CATEGORY CODE |
|---|
| Subject category code |
TJK |
| Source |
thema |
| 082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER |
|---|
| Classification number |
621.382 |
| Edition number |
23 |
| Item number |
UNP.J |
| 100 1# - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Unpingco, Jose. |
| Relator term |
Author |
| 9 (RLIN) |
33933 |
| 245 10 - TITLE STATEMENT |
|---|
| Title |
Python for probability, statistics and machine learning / |
| Statement of responsibility, etc. |
by Jose Unpingco. |
| Medium |
English. |
| 250 ## - EDITION STATEMENT |
|---|
| Edition statement |
3rd. |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. |
|---|
| Place of publication, distribution, etc. |
Switzerland : |
| Name of publisher, distributor, etc. |
Springer, |
| Date of publication, distribution, etc. |
2022. |
| 264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE |
|---|
| Name of producer, publisher, distributor, manufacturer |
: |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
xvii, 509 p. |
| Dimensions |
24 cm. |
| 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 |
| 365 ## - TRADE PRICE |
|---|
| Price amount |
89.99 |
| Currency code |
Euro |
| 505 0# - FORMATTED CONTENTS NOTE |
|---|
| Formatted contents note |
Getting Started with Scientific Python -- Probability -- Statistics -- Machine Learning -- Notation. |
| 520 ## - SUMMARY, ETC. |
|---|
| Summary, etc. |
This book covers the key ideas that link probability, statistics, and machine learning illustrated using Python modules in these areas. The entire text, including all the figures and numerical results, is reproducible using the Python codes and their associated Jupyter/IPython notebooks, which are provided as supplementary downloads. The author develops key intuitions in machine learning by working meaningful examples using multiple analytical methods and Python codes, thereby connecting theoretical concepts to concrete implementations. Modern Python modules like Pandas, Sympy, and Scikit-learn are applied to simulate and visualize important machine learning concepts like the bias/variance trade-off, cross-validation, and regularization. Many abstract mathematical ideas, such as convergence in probability theory, are developed and illustrated with numerical examples. This book is suitable for anyone with an undergraduate-level exposure to probability, statistics, or machine learning and with rudimentary knowledge of Python programming. Explains how to simulate, conceptualize, and visualize random statistical processes and apply machine learning methods; Connects to key open-source Python communities and corresponding modules focused on the latest developments in this area; Outlines probability, statistics, and machine learning concepts using an intuitive visual approach, backed up with corresponding visualization codes. |
| 588 ## - SOURCE OF DESCRIPTION NOTE |
|---|
| Source of description note |
Description based on publisher-supplied MARC data. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Applied mathematics. |
| 9 (RLIN) |
2749 |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Data mining. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Electrical engineering. |
| 9 (RLIN) |
32721 |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Engineering mathematics. |
| 9 (RLIN) |
2751 |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Mathematical statistics. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Statistics. |
| 650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Communications Engineering, Networks. |
| Authority record control number or standard number |
https://scigraph.springernature.com/ontologies/product-market-codes/T24035 |
| 9 (RLIN) |
33934 |
| 650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Data Mining and Knowledge Discovery. |
| Authority record control number or standard number |
https://scigraph.springernature.com/ontologies/product-market-codes/I18030 |
| 9 (RLIN) |
33935 |
| 650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Mathematical and Computational Engineering. |
| Authority record control number or standard number |
https://scigraph.springernature.com/ontologies/product-market-codes/T11006 |
| 9 (RLIN) |
2760 |
| 650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Probability and Statistics in Computer Science. |
| Authority record control number or standard number |
https://scigraph.springernature.com/ontologies/product-market-codes/I17036 |
| 9 (RLIN) |
33936 |
| 650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences. |
| Authority record control number or standard number |
https://scigraph.springernature.com/ontologies/product-market-codes/S17020 |
| 9 (RLIN) |
30258 |
| 776 08 - ADDITIONAL PHYSICAL FORM ENTRY |
|---|
| Relationship information |
Print version: |
| Title |
Python for probability, statistics, and machine learning. |
| International Standard Book Number |
9783319307152 |
| Record control number |
(DLC) 2016933108 |
| 776 08 - ADDITIONAL PHYSICAL FORM ENTRY |
|---|
| Relationship information |
Printed edition: |
| International Standard Book Number |
9783319307152 |
| 776 08 - ADDITIONAL PHYSICAL FORM ENTRY |
|---|
| Relationship information |
Printed edition: |
| International Standard Book Number |
9783319307169 |
| 906 ## - LOCAL DATA ELEMENT F, LDF (RLIN) |
|---|
| a |
0 |
| b |
ibc |
| c |
origres |
| d |
u |
| e |
ncip |
| f |
20 |
| g |
y-gencatlg |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Source of classification or shelving scheme |
|
| Koha item type |
Books |
| Edition |
23 |
| Suppress in OPAC |
No |