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Interpretable Machine Learning with Python: Learn to build interpretable high-performance models with hands-on real-world examples
Interpretable Machine Learning with Python: Learn to build interpretable high-performance models with hands-on real-world examples

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Biografía del autor Serg Masís has been at the confluence of the internet, application development, and analytics for the last two decades. Currently, he's a Climate and Agronomic Data Scientist at Syngenta, a leading agribusiness company with a mission to improve global food security. Before that role, he co-founded a startup, incubated by Harvard Innovation Labs, that combined the power of cloud computing and machine learning with principles in decision-making science to expose users to new places and events. Whether it pertains to leisure activities, plant diseases, or customer lifetime value, Serg is passionate about providing the often-missing link between data and decision-making - and machine learning interpretation helps bridge this gap more robustly.
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  • ISBN13 9781800203907
  • ISBN10 180020390X
  • Fecha de publicación 08/05/2026
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Interpretable Machine Learning with Python: Learn to build interpretable high-performance models with hands-on real-world examples

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