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The AI Dream Team: Strategies for ML Recruitment and Growth // Jelmer Borst and Daniela Solis // #267

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Organizing Data Science Teams for Success

This chapter addresses the complexities of organizing data science teams and emphasizes a centralized approach to machine learning recruitment and development. It highlights the necessity of clean data for effective model deployment and the importance of collaboration between engineering and business teams to align with business objectives. The discussion further explores the integration of data engineering and machine learning processes, stressing the value of strategic adaptability and informed decision-making.

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