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You're reading from  Interpretable Machine Learning with Python - Second Edition

Product typeBook
Published inOct 2023
PublisherPackt
ISBN-139781803235424
Edition2nd Edition
Concepts
Machine Learning
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Author (1)
Serg Masís
Serg Masís
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Serg Masís

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 start-up, 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 robustly.
Read more about Serg Masís

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Mission accomplished

The mission was to understand why one of your client’s bars is Outstanding while another one is Disappointing. Your approach employed the interpretation of machine learning models to arrive at the following conclusions:

  • According to SHAP on the tabular model, the Outstanding bar owes that rating to its berry taste and its cocoa percentage of 70%. On the other hand, the unfavorable rating for the Disappointing bar is due mostly to its earthy flavor and bean country of origin (Other). Review date plays a smaller role, but it seems that chocolate bars reviewed in that period (2013–15) were at an advantage.
  • LIME confirms that cocoa_percent<=70 is a desirable property, and that, in addition to berry, creamy, cocoa, and rich are favorable tastes, while sweet, sour, and molasses are unfavorable.
  • The commonality between both methods using the tabular model is that despite the many non-taste-related attributes, taste features are...
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Interpretable Machine Learning with Python - Second Edition
Published in: Oct 2023Publisher: PacktISBN-13: 9781803235424
© 2023 Packt Publishing Limited All Rights Reserved

Author (1)

author image
Serg Masís

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 start-up, 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 robustly.
Read more about Serg Masís

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