Continuous machine learning with Kubeflow : (Record no. 11064)

MARC details
000 -LEADER
fixed length control field 01621nam a22002657i 4500
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20250722113258.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 250722s |||ao||| |||| 00| 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9789389898507
040 ## - CATALOGING SOURCE
Original cataloging agency EG-GaU‬‬
Transcribing agency EG-GaU‬‬
Modifying agency EG-GaU‬‬
Description conventions rda
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Edition number 23
Classification number 006.3
Item number c.a.c.
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Choudhury, Aniruddha,
Relator term author.
9 (RLIN) 60426
245 10 - TITLE STATEMENT
Title Continuous machine learning with Kubeflow :
Remainder of title performing reliable MLOps with capabilities of TFX, Sagemaker and Kubernetes /
Statement of responsibility, etc. Aniruddha Choudhury.
250 ## - EDITION STATEMENT
Edition statement 1st edition.
264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE
Place of production, publication, distribution, manufacture New Delhi :
Name of producer, publisher, distributor, manufacturer BPB Publications,
Date of production, publication, distribution, manufacture, or copyright notice 2021.
300 ## - PHYSICAL DESCRIPTION
Extent 330 pages :
Other physical details illustrations ;
Dimensions 20 cm.
336 ## - CONTENT TYPE
Source rdacontent
Content type term text
Content type code txt
337 ## - MEDIA TYPE
Source rdamedia
Media type term unmediated
Media type code n
338 ## - CARRIER TYPE
Source rdacarrier
Carrier type term volume
Carrier type code nc
504 ## - BIBLIOGRAPHY, ETC. NOTE
Bibliography, etc. note Includes bibliographical references.<br/>
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note 1. Introduction to Kubeflow & Kubernetes cloud architecture ‡ 2. Developing Kubeflow pipeline in GCP ‡ 3. Designing computer vision model in Kubeflow ‡ 4. Building TFX pipeline ‡ 5. ML model explainability & interpretability ‡ 6. Building Weights & Biases pipeline development ‡ 7. Applied ML with AWS SageMaker ‡ 8. Web app development with Streamlit & Heroku.<br/>
520 ## - SUMMARY, ETC.
Summary, etc. Practical guide to deploying and managing continuous ML pipelines using Kubeflow on Kubernetes. Covers TFX, SageMaker, Explainable AI, and cloud deployments with Docker, GCP, AWS, and Heroku. Ideal for MLOps/devops engineers and data scientists. :contentReference[oaicite:1]{index=1}<br/>
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Machine learning
General subdivision Implementation.
9 (RLIN) 60427
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme Dewey Decimal Classification
Koha item type Books
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Home library Current library Shelving location Date acquired Total Checkouts Full call number Barcode Date last seen Copy number Price effective from Koha item type
    Dewey Decimal Classification     Media and mass communication Library Media and mass communication Library B4 08/19/2025   006.03 a.s.f MA0002286 08/19/2025 C.1 08/19/2025 Books