mplementing MLOps in the enterprise: (Record no. 200022)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 01950nam a22002417a 4500 |
| 003 - CONTROL NUMBER IDENTIFIER | |
| control field | OSt |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20260602162331.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 260602b |||||||| |||| 00| 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| ISBN | 978-9355426543 |
| -- | 9355426542 |
| 041 ## - LANGUAGE CODE | |
| Language code of text/sound track or separate title | eng |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Classification number | 006.31 HAV-I |
| 100 ## - MAIN ENTRY--AUTHOR NAME | |
| Personal name | Haviv, Yaron |
| 245 ## - TITLE STATEMENT | |
| Title | mplementing MLOps in the enterprise: |
| Remainder of title | a production-first approach |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) | |
| Place of publication | Mumbai |
| Name of publisher | Shroff Publishers & Distributors Pvt. Ltd. |
| Year of publication | 2023 |
| 300 ## - PHYSICAL DESCRIPTION | |
| Number of Pages | xiv, 361p. |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc | This practical guide helps your company bring data science to life for different real-world MLOps scenarios. Senior data scientists, MLOps engineers, and machine learning engineers will learn how to tackle challenges that prevent many businesses from moving ML models to production.<br/><br/>Authors Yaron Haviv and Noah Gift take a production-first approach. Rather than beginning with the ML model, you'll learn how to design a continuous operational pipeline, while making sure that various components and practices can map into it. By automating as many components as possible, and making the process fast and repeatable, your pipeline can scale to match your organization's needs.<br/><br/>You'll learn how to provide rapid business value while answering dynamic MLOps requirements. This book will help you:<br/><br/>Learn the MLOps process, including its technological and business value<br/>Build and structure effective MLOps pipelines<br/>Efficiently scale MLOps across your organization<br/>Explore common MLOps use cases<br/>Build MLOps pipelines for hybrid deployments, real-time predictions, and composite AI<br/>Learn how to prepare for and adapt to the future of MLOps<br/>Effectively use pre-trained models like HuggingFace and OpenAI to complement your MLOps strategy |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical Term | Artificial Intelligence |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical Term | Machine learning |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical Term | Machine learning operations |
| General subdivision | MLOps |
| 700 ## - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Gift, Noah |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | Books and Monographs |
| Full call number | Accession Number | Koha item type | Lost status | Damaged status | Permanent Location | Current Location | Shelving location | Date acquired | Source of acquisition |
|---|---|---|---|---|---|---|---|---|---|
| 006.31 HAV-I | 102857 | Books and Monographs | Central Library, NIT Jalandhar | Central Library, NIT Jalandhar | General Stacks | 20.05.2026 | Mumbai, TV Enterprises | ||
| 006.31 HAV-I | 102858 | Books and Monographs | Central Library, NIT Jalandhar | Central Library, NIT Jalandhar | General Stacks | 20.05.2026 | Mumbai, TV Enterprises | ||
| 006.31 HAV-I | 102859 | Books and Monographs | Central Library, NIT Jalandhar | Central Library, NIT Jalandhar | General Stacks | 20.05.2026 | Mumbai, TV Enterprises | ||
| 006.31 HAV-I | 102860 | Books and Monographs | Central Library, NIT Jalandhar | Central Library, NIT Jalandhar | General Stacks | 20.05.2026 | Mumbai, TV Enterprises | ||
| 006.31 HAV-I | 102861 | Books and Monographs | Central Library, NIT Jalandhar | Central Library, NIT Jalandhar | General Stacks | 20.05.2026 | Mumbai, TV Enterprises |