Deep Learning in Production
Sergios Karagiannakos
Deep Learning research is advancing rapidly over the past years. Frameworks and libraries are constantly been developed and updated. However, we still lack standardized solutions on how to serve, deploy and scale Deep Learning models. Deep Learning infrastructure is not very mature yet.
This book accumulates a set of best practices and approaches on how to build robust and scalable machine learning applications. It covers the entire lifecycle from data processing and training to deployment and maintenance. It will help you understand how to transfer methodologies that are generally accepted and applied in the software community, into Deep Learning projects.
It's an excellent choice for researchers with a minimal software background, software engineers with little experience in machine learning, or aspiring machine learning engineers.
This book accumulates a set of best practices and approaches on how to build robust and scalable machine learning applications. It covers the entire lifecycle from data processing and training to deployment and maintenance. It will help you understand how to transfer methodologies that are generally accepted and applied in the software community, into Deep Learning projects.
It's an excellent choice for researchers with a minimal software background, software engineers with little experience in machine learning, or aspiring machine learning engineers.
Categorías:
Año:
2022
Editorial:
Leanpub
Idioma:
english
Páginas:
209
ISBN 10:
6180033773
ISBN 13:
9786180033779
Archivo:
PDF, 29.32 MB
IPFS:
,
english, 2022