| 000 -LEADER |
|---|
| fixed length control field |
04191nam a22003137a 4500 |
| 003 - CONTROL NUMBER IDENTIFIER |
|---|
| control field |
OSt |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
|---|
| control field |
20250911110011.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
|---|
| fixed length control field |
250911s20242024 a|||er|||| 001 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
|---|
| International Standard Book Number |
9781394213054 [paperback] |
| 040 ## - CATALOGING SOURCE |
|---|
| Original cataloging agency |
University of Cebu-Banilad |
| Transcribing agency |
University of Cebu-Banilad |
| 100 ## - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Jay, Rabi, |
| Relator term |
author. |
| 245 ## - TITLE STATEMENT |
|---|
| Title |
Enterprise AI in the cloud : |
| Remainder of title |
a practical guide to deploying end-to-end machine learning and chatGPT™ solutions / |
| Statement of responsibility, etc |
Rabi Jay. |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) |
|---|
| Place of publication, distribution, etc |
Hoboken, New Jersey : |
| Name of publisher, distributor, etc |
John Wiley and Sons, Inc., |
| Date of publication, distribution, etc |
c2024. |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
xx, 504 pages : |
| Other physical details |
illustrations (black and white) ; |
| Dimensions |
23 cm. |
| 336 ## - CONTENT TYPE |
|---|
| Source |
rdacontent |
| Content type term |
text |
| 337 ## - MEDIA TYPE |
|---|
| Source |
rdamedia |
| Media type term |
unmediated |
| 338 ## - CARRIER TYPE |
|---|
| Source |
rdacarrier |
| Carrier type |
volume |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE |
|---|
| Bibliography, etc |
Includes index. |
| 505 ## - FORMATTED CONTENTS NOTE |
|---|
| Formatted contents note |
Contents: Part I Introduction 3 -- Part II Strategizing and assessing for AI 31 -- Part III Planning and launching a pilot project 79 -- Part IV Building and governing your team 163 -- Part V Setting up infrastructure and managing operations 187 -- Part VI Processing data and modeling 243 -- Part VII Deploying and monitoring models 345 -- Part VIII Scaling and transforming AI 391 -- Part IX Evolving and maturing AI 433 -- Index 485. |
| 520 ## - SUMMARY, ETC. |
|---|
| Summary, etc |
"Enterprise AI in the Cloud: A Practical Guide to Deploying End-to-End Machine Learning and ChatGPT Solutions is an indispensable resource for professionals and companies who want to bring new AI technologies like generative AI, ChatGPT, and machine learning (ML) into their suite of cloud-based solutions. If you want to set up AI platforms in the cloud quickly and confidently and drive your business forward with the power of AI, this book is the ultimate go-to guide. The author shows you how to start an enterprise-wide AI transformation effort, taking you all the way through to implementation, with clearly defined processes, numerous examples, and hands-on exercises. You'll also discover best practices on optimizing cloud infrastructure for scalability and automation. Enterprise AI in the Cloud helps you gain a solid understanding of: AI-First Strategy: Adopt a comprehensive approach to implementing corporate AI systems in the cloud and at scale, using an AI-First strategy to drive innovation. State-of-the-Art Use Cases: Learn from emerging AI/ML use cases, such as ChatGPT, VR/AR, blockchain, metaverse, hyper-automation, generative AI, transformer models, Keras, TensorFlow in the cloud, and quantum machine learning. Platform Scalability and MLOps (ML Operations): Select the ideal cloud platform and adopt best practices on optimizing cloud infrastructure for scalability and automation AWS, Azure, Google ML: Understand the machine learning lifecycle, from framing problems to deploying models and beyond, leveraging the full power of Azure, AWS, and Google Cloud platforms. AI-Driven Innovation Excellence: Get practical advice on identifying potential use cases, developing a winning AI strategy and portfolio, and driving an innovation culture. Ethical and Trustworthy AI Mastery: Implement Responsible AI by avoiding common risks while maintaining transparency and ethics. Scaling AI Enterprise-Wide: Scale your AI implementation using Strategic Change Management, AI Maturity Models, AI Center of Excellence, and AI Operating Model. Whether you're a beginner or an experienced AI or MLOps engineer, business or technology leader, or an AI student or enthusiast, this comprehensive resource empowers you to confidently build and use AI models in production, bridging the gap between proof-of-concept projects and real-world AI deployments. With over 300 review questions, 50 hands-on exercises, templates, and hundreds of best practice tips to guide you through every step of the way, this book is a must-read for anyone seeking to accelerate AI transformation across their enterprise." -- Provided by publisher. |
| 521 ## - TARGET AUDIENCE NOTE |
|---|
| Target audience note |
Adult |
| 541 ## - IMMEDIATE SOURCE OF ACQUISITION NOTE |
|---|
| Source of acquisition |
Purchased |
| Deans/Chairperson |
Ortega, Eric |
| Department |
College of Computer Studies |
| Subject Category |
Computer Studies : Information Technology |
| 546 ## - LANGUAGE NOTE |
|---|
| Language note |
Text in English |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Machine Learning |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Artificial Intelligence |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Source of classification or shelving scheme |
|
| Type of record |
Book |
| 998 ## - LOCAL CONTROL INFORMATION (RLIN) |
|---|
| Encoded by |
Janna [new] |
| Date encoded |
09/11/2025 |
