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What Every Aspiring Machine Learning Engineer Must Know to Succeed | by Claudia Ng | Dec, 2024


Your Information to Avoiding Important Errors with Machine Learning in Manufacturing

Picture by GrumpyBeere from Pixabay

I’ll always remember the primary time I received a PagerDuty alert telling me that mannequin scores weren’t being returned correctly in manufacturing.

Panic set in — I had simply accomplished a deploy, and my thoughts began racing with questions:

  • Did my code trigger a bug?
  • Is the error inflicting an outage downstream?
  • What a part of the code might be throwing errors?

Debugging dwell methods is aggravating, and I discovered a crucial lesson: writing production-ready code is a very totally different beast from writing code that works in a Jupyter Pocket book.

In 2020, I made the leap from information analyst to machine studying engineer (MLE). Whereas I used to be already proficient in SQL and Python, working with manufacturing methods compelled me to stage up my expertise.

As an analyst, I largely cared that my code ran and produced the proper output. This mindset not translated effectively to being an MLE.

As an MLE, I rapidly realized I had to give attention to writing environment friendly, clear, and maintainable code that labored in a shared codebase.



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