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Overview
Overview
Investing in AI in your company is more than developing cool algorithms, it s about balancing your efforts between data engineering, model development and AI operations. This book explains how to successfully operate AI from a life cycle perspective including key aspects for effectively navigating security and data rights, but also the importance of trustworthiness and ethical considerations in AI.
- An overview of the AI model life cycle - this part explains the total scope of what the AI investment needs to cater for and why
- The importance of efficient Data Engineering - without data the AI model can t run - still companies invest much less time and money on managing their data, than they do on developing new algorithms
- AI model development from an operational perspective - although AI models are developed and trained in the lab, that s not where they will generate value. This part will explain how to be more successful by adopting an operational approach already in the AI model development phase.
- Operating AI is different from operating SW - AI is built on continuous learning and therefore another operational support model is needed. The feedback loop becomes fundamental, along with highly automated monitoring of model performance and data quality.
- Resilient and secure AI solutions - addressing security aspects in your AI architecture should be considered from the get-go
- AI is all about Trust - what does it mean to build trustworthy AI solutions and to operate your AI solutions in a reliable manner
- Operationalizing a Business Model - how do you industrialize your AI business idea (including learnings from all previous chapters) - moving it from the concept phase, through exploration and development to finally being able to operate it in a live setting (internal or commercial).
- Format: Trade Paperback
- Author: Jagare, Ulrika
- ISBN: 9781119833192
- Condition: Used
- Publication Year: 2022
Language:
English