Grasp how to deliver fully deployed and scalable, trusted and responsible AI and avoid expensive failed solutions and limited proof-of-concepts with this practical guide covering the lifecyle process of AI product development.
Grasp how to deliver fully deployed and scalable, trusted and responsible AI and avoid expensive failed solutions and limited proof-of-concepts with this practical guide covering the lifecyle process of AI product development.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Eva-Marie Muller-Stuler is a senior data science and AI leader and sought-after advisor with over 23 years of industry experience and extensive expertise in leading ground-breaking data science teams and implementations of fully deployed large-scale and global AI projects at leading organizations. She has been recognised as one of The Best Data Scientists in the World by CNVRG and as one of the top 10 Most Influential Women in Technology by Analytics Insights. She advises governments and international bodies, such the United Nations (UN), UNESCO and International Congress for the Governance of AI (ICGAI) and works in collaboration with these bodies on developing a world-wide AI ethics framework. Muller-Stuler is Partner and Leader of the Data & AI practice for EY MENA and has held previous roles as Chief Technology Officer and Chief Data Scientist at IBM and Chief Data Scientist at KPMG. She has led numerous AI deployments and pioneered new concepts and methodologies, such as the Integrated Centre of Excellence strategies, the 7 pillars for successful AI, connected ecosystems with over 10K data signals, new feature engineering techniques and modelling approaches. Muller-Stuler is also a passionate supporter of women in technology and is a mentor, ambassador and co-host of Women in Data Science (WiDS). She is based in Dubai, UAE.
Inhaltsangabe
Chapter 01: Introduction What is AI product development; Chapter 02: Overview of ethical and responsible AI requirements; Chapter 03: How to assess the problem; Chapter 04: Risk management and mitigation; Chapter 05: Data management; Chapter 06: Team structure and processes; Chapter 07: Development for deployment; Chapter 08: Monitoring; Chapter 09: AI governance and compliance; Chapter 10: Maintaining for the future
Chapter 01: Introduction What is AI product development; Chapter 02: Overview of ethical and responsible AI requirements; Chapter 03: How to assess the problem; Chapter 04: Risk management and mitigation; Chapter 05: Data management; Chapter 06: Team structure and processes; Chapter 07: Development for deployment; Chapter 08: Monitoring; Chapter 09: AI governance and compliance; Chapter 10: Maintaining for the future
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