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Machine Learning Logistics

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  • 89 páginas
  • 4 horas de lectura

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Machine learning offers a rich potential for expanding the way wework with data and the value we can mine from it. To do this well inserious production settings, it’s essential to be able to manage theoverall flow of data and work, not only in a single project, but alsoacross organizations.This book is for anyone who wants to know more about gettingmachine learning model management right in the real world,including data scientists, architects, developers, operations teams,and project managers. Topics we discuss and the solutions we proposeshould be helpful for readers who are highly experienced withmachine learning or deep learning as well as for novices. You don’tneed a background in statistics or mathematics to take advantage ofmost of the content, with the exception of evaluation and metricsanalysis.

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Machine Learning Logistics, Ted Dunning, Ellen Friedman

Idioma
Publicado en
2017
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Título
Machine Learning Logistics
Idioma
Inglés
Publicado en
2017
Formato
Tapa blanda
Páginas
89
ISBN10
1491997591
ISBN13
9781491997598
Serie
Descripción
Machine learning offers a rich potential for expanding the way wework with data and the value we can mine from it. To do this well inserious production settings, it’s essential to be able to manage theoverall flow of data and work, not only in a single project, but alsoacross organizations.This book is for anyone who wants to know more about gettingmachine learning model management right in the real world,including data scientists, architects, developers, operations teams,and project managers. Topics we discuss and the solutions we proposeshould be helpful for readers who are highly experienced withmachine learning or deep learning as well as for novices. You don’tneed a background in statistics or mathematics to take advantage ofmost of the content, with the exception of evaluation and metricsanalysis.