Experimentation in Data Science
Matthew emphasizes the importance of establishing a solid foundation for data representation and the need for a robust experimental infrastructure. He advocates for maximizing the number of experiments run over time, highlighting that a well-configured test harness can significantly speed up the iteration process. The ultimate goal is to enhance user experience by understanding their needs and continuously improving the app's personalization features.In this clip
From this podcast
Super Data Science: ML & AI Podcast with Jon Krohn
SDS 545: Scaling Data-Intensive Real-Time Applications — with Matthew Russell
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