753: Blend Any Programming Languages in Your ML Workflows, with Dr. Greg Michaelson
Super Data Science: ML & AI Podcast with Jon Krohn
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Challenges and Evolving Roles in AI Projects
The chapter explores the reasons behind AI project failures, including misalignment between data science and business teams, implementation challenges, and misconceptions about deploying multiple machine learning models. It discusses the difficulties in maintaining machine learning models in production, the rise of MLOps, and the expanding role of data scientists beyond model training. Additionally, it delves into the evolution of data science careers, emphasizing the need for practical skills and continuous learning, and emphasizes the importance of aligning technical expertise with a deep understanding of the business for successful AI implementations.
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