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Explore rapid feature harvesting techniques using Deep Feature Synthesis (DFS) and data engineering in this conference talk from YOW! 2019. Discover how automating feature engineering can significantly reduce time-to-market for classical machine learning models. Learn about the core constructs of DFS, implemented in the FeatureTools Python package, and its support for time dimensions. Gain insights into enhancing the base algorithm for broader use cases. Delve into the potential of DFS to revolutionize feature engineering, a critical component in model development. Understand how these techniques can be applied to various business models and machine learning applications, potentially transforming the efficiency of your data science projects.
