10 Standards of coding and creating maintainable ML code

This chapter covers

  • Identifying ML code smells and how to correct them
  • Reducing code complexity in ML projects
  • Currying for cleaner and more understandable code
  • Applying proper exception handling in ML code bases
  • Understanding side effects and how they can create bugs
  • Simplifying nested logic to improve comprehension

In the preceding chapter, we covered the broad strokes of a code foundation. Focusing on breaking up complex structure by utilizing refactoring and basic software-engineering best practices was important to pave the way for further discussion of the more detailed aspects of software development for ML. Without laying the foundation of basic best-practices, the code architecture ...

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