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Explore the critical role of feature engineering in machine learning and data science through this insightful conference talk from EuroPython 2018. Delve into the process of transforming raw data into meaningful features that better represent underlying problems, leading to improved model accuracy. Learn about feature selection techniques, develop a simple yet powerful ensemble for measuring feature importance, and understand how to apply these concepts to real-world datasets. Gain valuable insights into why good features often outperform complex algorithms in machine learning projects. Suitable for those with intermediate Python programming skills and basic knowledge of machine learning concepts.