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

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Published inOct 2023
PublisherPackt
ISBN-139781803235424
Edition2nd Edition
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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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References

  • Wilson, D.R., & Martinez, T. (1997). Improved Heterogeneous Distance Functions. J. Artif. Int. Res. 6-1. pp.1-34.https://arxiv.org/abs/cs/9701101
  • Morris, M. (1991). Factorial sampling plans for preliminary computational experiments. Quality Engineering, 37, 307-310. https://doi.org/10.2307%2F1269043
  • Saltelli, A., Tarantola, S., Campolongo, F., & Ratto, M. (2007). Sensitivity analysis in practice: A guide to assessing scientific models. Chichester: John Wiley & Sons.
  • Sobol, I.M. (2001), Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates. MATH COMPUT SIMULAT,55(1–3),271-280 https://doi.org/10.1016/S0378-4754(00)00270-6
  • Saltelli, A., P. Annoni, I. Azzini, F. Campolongo, M. Ratto, and S. Tarantola (2010). "Variance based sensitivity analysis of model output. Design and estimator for the total sensitivity index." Computer Physics Communications, 181(2):259-270. https://doi.org/10.1016/j.cpc.2009.09.018
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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