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A Framework for Feature Engineering and Machine Learning Pipelines

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Best practices on structuring ML projects - Jacques Peeters

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Some best practices on how to structure feature engineering and machine learning pipelines

The goal of the talk is to give some tips on how to avoid the following pitfalls:

  • Spaghetti code
  • Long debugging
  • Asymmetries between training and inference

You will learn how to:

  • Enhance code maintainability
  • Improve iteration speed
  • Make the transition to production easier

About the speaker:

Jacques Peeters is a lead data scientist at ManoMano, a European home improvement marketplace. He tackles various topics such as recsys, sales forecasting, bidding algorithms, customer targeting.

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