AI Lifecycle Management
Organizations must recognize that machine learning models require continuous monitoring and alignment with business goals. Effective decision-making structures and an understanding of the necessary data and technology are crucial. The iterative nature of the AI lifecycle demands ongoing involvement, especially as technological advancements and regulations evolve rapidly. A robust framework has been developed to guide companies in implementing AI strategically, emphasizing the importance of management and business impact.In this clip
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Super Data Science: ML & AI Podcast with Jon Krohn
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