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You're reading from  Practical Deep Learning at Scale with MLflow

Product typeBook
Published inJul 2022
PublisherPackt
ISBN-139781803241333
Edition1st Edition
Concepts
Deep Learning
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Author (1)
Yong Liu
Yong Liu
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Yong Liu

Yong Liu has been working in big data science, machine learning, and optimization since his doctoral student years at the University of Illinois at Urbana-Champaign (UIUC) and later as a senior research scientist and principal investigator at the National Center for Supercomputing Applications (NCSA), where he led data science R&D projects funded by the National Science Foundation and Microsoft Research. He then joined Microsoft and AI/ML start-ups in the industry. He has shipped ML and DL models to production and has been a speaker at the Spark/Data+AI summit and NLP summit. He has recently published peer-reviewed papers on deep learning, linked data, and knowledge-infused learning at various ACM/IEEE conferences and journals.
Read more about Yong Liu

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Understanding the categories and audience of explainability

As this chapter's opening texts imply, explainability for a DL system becomes increasingly critical, sometimes even mandatory, in highly regulated industries such as financial, legal, governmental, and medical application domains. An example lawsuit partially due to the lack of ML explainability is the case of B2C2 v Quoine (https://www.scl.org/articles/12130-explainable-machine-learning-how-can-you-determine-what-a-party-knew-or-intended-when-a-decision-was-made-by-machine-learning), where automated AI trading algorithms mistakenly placed an order with 250 times the market price for bitcoin trading. The recent successful applications of DL models in production stimulate active and abundant research and development in the explainability area due to the need to understand why and how a DL model works. You may have heard of the term explainable artificial intelligence (XAI), which was started by the US Defense Advanced...

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Practical Deep Learning at Scale with MLflow
Published in: Jul 2022Publisher: PacktISBN-13: 9781803241333
© 2022 Packt Publishing Limited All Rights Reserved

Author (1)

author image
Yong Liu

Yong Liu has been working in big data science, machine learning, and optimization since his doctoral student years at the University of Illinois at Urbana-Champaign (UIUC) and later as a senior research scientist and principal investigator at the National Center for Supercomputing Applications (NCSA), where he led data science R&D projects funded by the National Science Foundation and Microsoft Research. He then joined Microsoft and AI/ML start-ups in the industry. He has shipped ML and DL models to production and has been a speaker at the Spark/Data+AI summit and NLP summit. He has recently published peer-reviewed papers on deep learning, linked data, and knowledge-infused learning at various ACM/IEEE conferences and journals.
Read more about Yong Liu

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