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Software Engineering Practices in Data Science Projects: Benefits and Considerations

🧵 The TL;DR

Data scientists need to be careful when introducing software engineering practices to their projects, as over-engineering can have a negative impact on productivity. Good coding practices such as descriptive variables, structured code, and functions/classes should be used.

    🔑 Key Points

  • Data science scripts are often exploratory in nature, so over-engineering can hurt productivity.
  • Version control and unit tests should only be used when the project reaches the appropriate stage.
  • Good coding practices should be incorporated for the best results.

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