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Welcome to the workshop!

Workshop
In Progress

Welcome to Feature Engineering Fundamentals in Practice!​

Today's icebreaker:​

What do these images have in common, and how does this relate to feature engineering?

Share your thoughts in the chat!

Today's agenda:​

  • **Review:**Recap key concepts.
  • **Practise:**Feature engineering for churn prediction.
  • **Closing:**Key takeaways and next steps.

Today's learning objectives:​

  • Identify basic data quality issues in a real-world dataset and apply appropriate data cleaning techniques to address them.
  • Apply encoding techniques to convert categorical variables into model-ready features.
  • Create new features that represent customer tenure segments, service usage levels and spend patterns to capture domain-specific insights.
  • Evaluate the impact of engineered features on machine learning model performance and interpretability.