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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
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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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The approach

The bank has stressed to you how important it is that there’s fairness embedded in your methods because the regulators and the public at large want assurance that banks will not cause any more harm. Their reputation depends on it too, because in recent months, the media has been relentless in blaming them for dishonest and predatory lending practices, causing distrust in consumers. For this reason, they want to use state-of-the-art robustness testing to demonstrate that the prescribed policies will alleviate the problem. Your proposed approach includes the following points:

  • Younger lenders have been reported to be more prone to defaulting on repayment, so you expect to find age bias, but you will also look for bias with other protected groups such as gender.
  • Once you have detected bias, you can mitigate bias with preprocessing, in-processing, and post-processing algorithms using the AI Fairness 360 (AIF360) library. In this process, you will train...
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Interpretable Machine Learning with Python - Second Edition
Published in: Oct 2023Publisher: PacktISBN-13: 9781803235424

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