MARC details
| 000 -LEADER |
|---|
| fixed length control field |
02432cam a2200373 i 4500 |
| 001 - CONTROL NUMBER |
|---|
| control field |
23049201 |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
|---|
| control field |
20240310114549.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
|---|
| fixed length control field |
230405t20222022caua f b 001 0 eng d |
| 010 ## - LIBRARY OF CONGRESS CONTROL NUMBER |
|---|
| LC control number |
2023275143 |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
|---|
| International Standard Book Number |
9781098107963 |
| Qualifying information |
(paperback) |
| 035 ## - SYSTEM CONTROL NUMBER |
|---|
| System control number |
(OCoLC)on1286145997 |
| 035 ## - SYSTEM CONTROL NUMBER |
|---|
| System control number |
(Sirsi) i9781098107963 |
| 040 ## - CATALOGING SOURCE |
|---|
| Original cataloging agency |
YDX |
| Language of cataloging |
eng |
| Transcribing agency |
YDX |
| Description conventions |
rda |
| Modifying agency |
BDX |
| -- |
UKMGB |
| -- |
CDX |
| -- |
UOK |
| -- |
OCLCF |
| -- |
OTP |
| -- |
DLC |
| 042 ## - AUTHENTICATION CODE |
|---|
| Authentication code |
lccopycat |
| 050 00 - LIBRARY OF CONGRESS CALL NUMBER |
|---|
| Classification number |
Q325.5 |
| Item number |
.H89 2022 |
| 082 00 - DEWEY DECIMAL CLASSIFICATION NUMBER |
|---|
| Classification number |
<a href="006.31">006.31</a> |
| 100 1# - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Huyen, Chip, |
| Relator term |
author |
| 9 (RLIN) |
3322 |
| 245 10 - TITLE STATEMENT |
|---|
| Title |
Designing machine learning systems : |
| Remainder of title |
an iterative process for production-ready applications |
| Statement of responsibility, etc. |
/ Chip Huyen. |
| 250 ## - EDITION STATEMENT |
|---|
| Edition statement |
First edition. |
| 264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE |
|---|
| Place of production, publication, distribution, manufacture |
Sebastopol, CA : |
| Name of producer, publisher, distributor, manufacturer |
O'Reilly Media, Inc., |
| Date of production, publication, distribution, manufacture, or copyright notice |
2022. |
| 264 #4 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE |
|---|
| Date of production, publication, distribution, manufacture, or copyright notice |
©2022 |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
xvi, 367 pages : |
| Other physical details |
illustrations; |
| Dimensions |
24 cm |
| 336 ## - CONTENT TYPE |
|---|
| Content type term |
still image |
| Content type code |
sti |
| Source |
rdacontent |
| 336 ## - CONTENT TYPE |
|---|
| Content type term |
text |
| Content type code |
txt |
| Source |
rdacontent |
| 337 ## - MEDIA TYPE |
|---|
| Media type term |
unmediated |
| Media type code |
n |
| Source |
rdamedia |
| 338 ## - CARRIER TYPE |
|---|
| Carrier type term |
volume |
| Carrier type code |
nc |
| Source |
rdacarrier |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE |
|---|
| Bibliography, etc. note |
Includes bibliographical references and index. |
| 505 00 - FORMATTED CONTENTS NOTE |
|---|
| Title |
Overview of machine learning systems -- |
| -- |
Introduction to machine learning systems design -- |
| -- |
Data engineering fundamentals -- |
| -- |
Training data -- |
| -- |
Feature Engineering -- |
| -- |
Model development and offline evaluation -- |
| -- |
Model develoypment and prediction service -- |
| -- |
Data distribution shifts and monitoring -- |
| -- |
Continual learning and test in production -- |
| -- |
Infrastructure and tooling for MLOps -- |
| -- |
The human side of machine learning |
| 520 ## - SUMMARY, ETC. |
|---|
| Summary, etc. |
"Machine learning systems are both complex and unique. Complex because they consist of many different components and involve many different stakeholders. Unique because they're data dependent, with data varying wildly from one use case to the next. In this book, you'll learn a holistic approach to designing ML systems that are reliable, scalable, maintainable, and adaptive to changing environments and business requirements. Author Chip Huyen, co-founder of Claypot AI, considers each design decision--such as how to process and create training data, which features to use, how often to retrain models, and what to monitor--in the context of how it can help your system as a whole achieve its objectives. The iterative framework in this book uses actual case studies backed by ample references."--Amazon.com. |
| 596 ## - |
|---|
| -- |
1 3 |
| 598 ## - |
|---|
| -- |
NEWBOOKS |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Application software |
| General subdivision |
Design |
| 9 (RLIN) |
3323 |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Machine learning. |
| 9 (RLIN) |
2745 |