1492083291
Introducing MLOps: How to Scale Machine Learning in the Enterprise eBooks & eLearning
Posted by hill0 at Feb. 1, 2021
Introducing MLOps: How to Scale Machine Learning in the Enterprise
by Mark Treveil
English | 2021 | ISBN: 1492083291 | 150 Pages | AZW3 | 2 MB
by Mark Treveil
English | 2021 | ISBN: 1492083291 | 150 Pages | AZW3 | 2 MB
Introducing MLOps: How to Scale Machine Learning in the Enterprise (Early Release) eBooks & eLearning
Posted by zxcvbn at May 23, 2020
Introducing MLOps: How to Scale Machine Learning in the Enterprise (Early Release)
Clément Stenac | 2020 | ISBN: 1492083291 | 150 pages | EPUB, PDF(conv) | 2.7 MB, 2.9 MB
Clément Stenac | 2020 | ISBN: 1492083291 | 150 pages | EPUB, PDF(conv) | 2.7 MB, 2.9 MB
Introducing MLOps: How to Scale Machine Learning in the Enterprise eBooks & eLearning
Posted by yoyoloit at Aug. 23, 2021
Introducing MLOps
by Treveil, Mark; Omont, Nicolas; Stenac, Clément
English | 2021 | ISBN: 1492083291 | 186 pages | True PDF | 13.61 MB
by Treveil, Mark; Omont, Nicolas; Stenac, Clément
English | 2021 | ISBN: 1492083291 | 186 pages | True PDF | 13.61 MB
Introducing MLOps: How to Scale Machine Learning in the Enterprise eBooks & eLearning
Posted by hill0 at Dec. 1, 2020
Introducing MLOps: How to Scale Machine Learning in the Enterprise
by Mark Treveil
English | 2021 | ISBN: 1492083291 | 150 Pages | EPUB | 5.47 MB
by Mark Treveil
English | 2021 | ISBN: 1492083291 | 150 Pages | EPUB | 5.47 MB
Introducing MLOps: How to Scale Machine Learning in the Enterprise eBooks & eLearning
Posted by First1 at Dec. 11, 2020
Introducing MLOps: How to Scale Machine Learning in the Enterprise by Mark Treveil, Nicolas Omont, Clément Stenac, Kenji Lefevre, Du Phan, Joachim Zentici, Adrien Lavoillotte, Makoto Miyazaki, Lynn Heidmann
English | November 30th, 2020 | ISBN: 1492083291 | 186 pages | True EPUB | 4.89 MB
English | November 30th, 2020 | ISBN: 1492083291 | 186 pages | True EPUB | 4.89 MB
More than half of the analytics and machine learning (ML) models created by organizations today never make it into production. Some of the challenges and barriers to operationalization are technical, but others are organizational. Either way, the bottom line is that models not in production can't provide business impact.