Chapter 10. Making an effective analysis

This chapter covers

  • Planning an analysis
  • Thinking through code, data, and project structure
  • Delivering the analysis to the client

This chapter is written in the context of data scientists who focus on decision science and analytics—people who use data to provide ideas and suggestions to the business. Although machine learning engineers also have to do analysis before building and deploying models, some of the content around stakeholder management with pretty visualizations is less relevant. If you’re a machine learning engineer and you’re reading this book, don’t worry; this chapter is still ...

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