Interpretable Machine Learning with Python: Learn to build interpretable high-performance models with hands-on real-world examples 1st Edition, Kindle Edition

4.9 out of 5 stars 31 ratings
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ISBN-13: 978-1800203907
ISBN-10: 180020390X
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From the Publisher

Editorial Reviews

About the Author

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.

--This text refers to the paperback edition.

Product details

  • ASIN ‏ : ‎ B08PDFXXRL
  • Publisher ‏ : ‎ Packt Publishing; 1st edition (March 26, 2021)
  • Publication date ‏ : ‎ March 26, 2021
  • Language ‏ : ‎ English
  • File size ‏ : ‎ 23465 KB
  • Text-to-Speech ‏ : ‎ Enabled
  • Screen Reader ‏ : ‎ Supported
  • Enhanced typesetting ‏ : ‎ Enabled
  • X-Ray ‏ : ‎ Not Enabled
  • Word Wise ‏ : ‎ Not Enabled
  • Print length ‏ : ‎ 736 pages
  • Page numbers source ISBN ‏ : ‎ 180020390X
  • Lending ‏ : ‎ Not Enabled
  • Customer Reviews:
    4.9 out of 5 stars 31 ratings

Customer reviews

4.9 out of 5 stars
4.9 out of 5
31 global ratings
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Reviewed in the United States on April 27, 2021
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Reviewed in the United States on August 2, 2021

Top reviews from other countries

ohdaesu
5.0 out of 5 stars Très bonne reference pour s'immerser dans le sujet du ML et Python
Reviewed in France on June 18, 2021
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5.0 out of 5 stars Très bonne reference pour s'immerser dans le sujet du ML et Python
Reviewed in France on June 18, 2021
Excellent point de depart pour s'introduire dans le monde du Machine Learning et pour se familiariser avec Python. Les examples son d'actualité et pertinents.
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