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Building Effective ML Teams Through Trust and Experimentation
The chapter emphasizes the importance of trust, communication, and diversity in building an effective ML team that can navigate complexities in modern product development. It discusses the need for experimentation within a team, using the analogy of managing trash in an apartment without a rubbish bin to highlight the importance of quickly discarding unproductive ideas. Additionally, it references existing literature to provide insights on building teams for complex environments and delves into the intersection of machine learning and software engineering, showcasing the significance of engineering practices like test-driven development.