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For those new to AI or AI in an enterprise setting you will find this book a systematic introduction to the field. You will get the necessary know-how to collaborate with and lead AI specialists and guide them to success. Time-pressured readers will benefit from self-contained sections explaining key topics and providing illustrations for fostering discussions in their next team, project, or management meeting. Reading this book helps you to better sell the business benefits from your AI initiatives and build your skills around scoping and delivering AI projects. You will be better able to work through critical aspects such as quality assurance, security, and ethics when building AI solutions in your organization.
Scope and manage AI projects in your organization
Set up quality assurance and testing for AI models and their integration in complex software solutions
Shape and manage an AI delivery organization, thereby mastering ML Ops
Understand and formulate requirements for the underlying data management infrastructure
Handle AI-related IT security, compliance, and risk topics and understand relevant AI ethics aspects
For those new to AI or AI in an enterprise setting you will find this book a systematic introduction to the field. You will get the necessary know-how to collaborate with and lead AI specialists and guide them to success. Time-pressured readers will benefit from self-contained sections explaining key topics and providing illustrations for fostering discussions in their next team, project, or management meeting. Reading this book helps you to better sell the business benefits from your AI initiatives and build your skills around scoping and delivering AI projects. You will be better able to work through critical aspects such as quality assurance, security, and ethics when building AI solutions in your organization.
Scope and manage AI projects in your organization
Set up quality assurance and testing for AI models and their integration in complex software solutions
Shape and manage an AI delivery organization, thereby mastering ML Ops
Understand and formulate requirements for the underlying data management infrastructure
Handle AI-related IT security, compliance, and risk topics and understand relevant AI ethics aspects
Shows how to manage AI projects and run an AI delivery organization in an enterprise or large organization
Helps data scientists to advance in their career into management roles
Enables experienced managers and IT professionals to transfer their skills to AI initiatives
1. Why Organizations Invest in AI.- 2. Structuring and Delivering AI Projects.- 3. Quality Assurance in and for AI.- 4. Ethics, Regulations, and Explainability.- 5. Building an AI Delivery Organization.- 6. AI & Data Management Architectures.- 7. Securing & Protecting AI Environments.- 8. Looking Forward.
| Erscheinungsjahr: | 2021 |
|---|---|
| Genre: | Importe, Informatik |
| Rubrik: | Naturwissenschaften & Technik |
| Medium: | Taschenbuch |
| Inhalt: |
xix
214 S. 96 s/w Illustr. 214 p. 96 illus. |
| ISBN-13: | 9781484278239 |
| ISBN-10: | 1484278232 |
| Sprache: | Englisch |
| Einband: | Kartoniert / Broschiert |
| Autor: | Haller, Klaus |
| Auflage: | 1st edition |
| Hersteller: |
Apress
Apress L.P. |
| Verantwortliche Person für die EU: | APress in Springer Science + Business Media, Heidelberger Platz 3, D-14197 Berlin, juergen.hartmann@springer.com |
| Maße: | 254 x 178 x 13 mm |
| Von/Mit: | Klaus Haller |
| Erscheinungsdatum: | 17.12.2021 |
| Gewicht: | 0,453 kg |