Machine learning logistics : model management in the real world /
To succeed with machine learning or deep learning, you must handle the logistics well. Simply put, you need an effective management system for overall data flow and the evaluation and deployment of multiple models as they move from prototype to production. Without that, your project will most likely...
Call Number: | Libro Electrónico |
---|---|
Main Authors: | Dunning, Ted, 1956- (Author), Friedman, B. Ellen (Author) |
Format: | Electronic eBook |
Language: | Inglés |
Published: |
Sebastopol, CA :
O'Reilly Media,
[2017]
|
Edition: | First edition. |
Subjects: | |
Online Access: | Texto completo (Requiere registro previo con correo institucional) |
Similar Items
-
Practical feature engineering /
Published: (2019) -
The evolution of analytics : opportunities and challenges for machine learning in business /
by: Hall, Patrick, et al.
Published: (2016) -
Machine learning and data monetization /
Published: (2019) -
Executive briefing : why machine-learned models crash and burn in production and what to do about it /
Published: (2019) -
Bringing data to life : combining machine learning and art to tell a data story /
Published: (2019)