Practicing Trustworthy Machine Learning, 9781098120276
Paperback
Build secure, fair, and robust ML models for a hostile world.

Practicing Trustworthy Machine Learning

Consistent, Transparent, and Fair AI Pipelines

$128.33

  • Paperback

    350 pages

  • Release Date

    13 January 2023

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Summary

With the increasing use of AI in high-stakes domains such as medicine, law, and defense, organizations spend a lot of time and money to make ML models trustworthy. Many books on the subject offer deep dives into theories and concepts. This guide provides a practical starting point to help development teams produce models that are secure, more robust, less biased, and more explainable.

Authors Yada Pruksachatkun, Matthew McAteer, and Subhabrata Majumdar translate best practices in the …

Book Details

ISBN-13:9781098120276
ISBN-10:1098120272
Author:Yada Pruksachatkun, Subhabrata Majumdar, Matthew McAteer
Publisher:O'Reilly Media
Imprint:O'Reilly Media
Format:Paperback
Number of Pages:350
Release Date:13 January 2023
Weight:535g
Dimensions:232mm x 178mm
About The Author

Yada Pruksachatkun

Yada Pruksachatkun is a machine learning scientist at Infinitus, a conversational AI startup that automates calls in the healthcare system. She has worked on trustworthy natural language processing as an Applied Scientist at Amazon, and led the first healthcare NLP initiative within mid-sized startup ASAPP. She did research transfer learning in NLP in graduate school at NYU and was advised by Professor Sam Bowman.

Matthew McAteer works on machine learning at Formic Labs, a startup focused on in silico cell simulation. He is also the creator of 5cube Labs, an ML consultancy that has worked with over 100 companies in industries ranging from architecture to medicine to agriculture. Matthew previously worked with the TensorFlow team at Google on probabilistic programming, and with the general-purpose AI research company Generally Intelligent. Before he was an ML engineer, Matthew worked in biomedical research labs at MIT, Harvard Medical School, and Brown University.

Subhabrata (Subho) Majumdar is a Senior Applied Scientist at Splunk. Previously, he spent 3 years in AT&T, where he led research and development on ethical AI. Subho deeply believes in the power of data to bring about positive changes in the world—he has cofounded the Trustworthy ML Initiative, and has been a part of multiple successful industry-academia collaborations in the data for good space. Subho holds a PhD in Statistics from the University of Minnesota.

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