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Navigating Data Science: From Simplicity to Complexity
This chapter highlights the significance of starting with simple models like logistic regression in data science before advancing to more complex techniques. It emphasizes the value of curiosity and collaboration in deriving meaningful insights from data, as well as the need for alignment between data scientists' motivations and business goals. Additionally, the discussion covers the importance of adaptive infrastructure and leadership support for sustainable data science practices.