Responsible AI in the Enterprise (notice n° 77492)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 03584cam a2200301zu 4500 |
| 003 - CONTROL NUMBER IDENTIFIER | |
| control field | FRCYB88946120 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20250108002206.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 250108s2023 fr | o|||||0|0|||eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 9781803230528 |
| 035 ## - SYSTEM CONTROL NUMBER | |
| System control number | FRCYB88946120 |
| 040 ## - CATALOGING SOURCE | |
| Original cataloging agency | FR-PaCSA |
| Language of cataloging | en |
| Transcribing agency | |
| Description conventions | rda |
| 100 1# - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Masood, Adnan |
| 245 01 - TITLE STATEMENT | |
| Title | Responsible AI in the Enterprise |
| Remainder of title | Practical AI risk management for explainable, auditable, and safe models with hyperscalers and Azure OpenAI |
| Statement of responsibility, etc. | ['Masood, Adnan', 'Dawe, Heather', 'Adeli, Dr. Ehsan'] |
| 264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE | |
| Name of producer, publisher, distributor, manufacturer | Packt Publishing |
| Date of production, publication, distribution, manufacture, or copyright notice | 2023 |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | p. |
| 336 ## - CONTENT TYPE | |
| Content type code | txt |
| Source | rdacontent |
| 337 ## - MEDIA TYPE | |
| Media type code | c |
| Source | rdamdedia |
| 338 ## - CARRIER TYPE | |
| Carrier type code | c |
| Source | rdacarrier |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc. | Build and deploy your AI models successfully by exploring model governance, fairness, bias, and potential pitfalls Purchase of the print or Kindle book includes a free PDF eBookKey FeaturesLearn ethical AI principles, frameworks, and governanceUnderstand the concepts of fairness assessment and bias mitigationIntroduce explainable AI and transparency in your machine learning modelsBook DescriptionResponsible AI in the Enterprise is a comprehensive guide to implementing ethical, transparent, and compliant AI systems in an organization. With a focus on understanding key concepts of machine learning models, this book equips you with techniques and algorithms to tackle complex issues such as bias, fairness, and model governance. Throughout the book, you’ll gain an understanding of FairLearn and InterpretML, along with Google What-If Tool, ML Fairness Gym, IBM AI 360 Fairness tool, and Aequitas. You’ll uncover various aspects of responsible AI, including model interpretability, monitoring and management of model drift, and compliance recommendations. You’ll gain practical insights into using AI governance tools to ensure fairness, bias mitigation, explainability, privacy compliance, and privacy in an enterprise setting. Additionally, you’ll explore interpretability toolkits and fairness measures offered by major cloud AI providers like IBM, Amazon, Google, and Microsoft, while discovering how to use FairLearn for fairness assessment and bias mitigation. You’ll also learn to build explainable models using global and local feature summary, local surrogate model, Shapley values, anchors, and counterfactual explanations. By the end of this book, you’ll be well-equipped with tools and techniques to create transparent and accountable machine learning models.What you will learnUnderstand explainable AI fundamentals, underlying methods, and techniquesExplore model governance, including building explainable, auditable, and interpretable machine learning modelsUse partial dependence plot, global feature summary, individual condition expectation, and feature interactionBuild explainable models with global and local feature summary, and influence functions in practiceDesign and build explainable machine learning pipelines with transparencyDiscover Microsoft FairLearn and marketplace for different open-source explainable AI tools and cloud platformsWho this book is forThis book is for data scientists, machine learning engineers, AI practitioners, IT professionals, business stakeholders, and AI ethicists who are responsible for implementing AI models in their organizations. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | |
| 700 0# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Masood, Adnan |
| 700 0# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Dawe, Heather |
| 700 0# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Adeli, Dr. Ehsan |
| 856 40 - ELECTRONIC LOCATION AND ACCESS | |
| Access method | Cyberlibris |
| Uniform Resource Identifier | <a href="https://international.scholarvox.com/netsen/book/88946120">https://international.scholarvox.com/netsen/book/88946120</a> |
| Electronic format type | text/html |
| Host name | |
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