Keras to Kubernetes: The Journey of a Machine Learning Model to Production/ by Dattaraj Rao

By:

Rao, Dattaraj [Author]

Material type: Text

TextPublisher: Hoboken : John Wiley & Sons, Incorporated 2019Description: xviii, 302 pages : illustrations ; 24 cmContent type:

text

Media type:

unmediated

Carrier type:

volume

ISBN:

9781119564836
1119564832

Subject(s):

LOC classification:

GS Q 325.5 R36 2019

Online resources:

Wiley-Blackwell

Contents:

Big data and artificial intelligence Machine learning Handling unstructured data Deep learning using Keras Advanced deep learning Cutting-edge deep learning projects AI in the modern software world Deploying AI models as microservices Machine learning development lifecycle A platform for machine learning

Summary: Artificial intelligence (AI) has, in one form or another, been in existence for over six decades. However, recent years have seen an enormous increase in the amount of collectable data and major advancements in algorithms and computer hardware. Within the realm of AI technology, machine learning (ML) and deep learning (DL) applications in particular have undergone significant growth Keras, one of the most popular DL frameworks, can quickly describe a DL model, begin training it on data, and generate more data by modifying existing data...

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Holdings
Item type	Current library	Shelving location	Call number	Status	Date due	Barcode
Book	TUP Manila Library	Graduate Program Section-2F	GS Q 325.5 R36 2019 (Browse shelf(Opens below))	Available		P00033753

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Includes index and bibliographical references

Artificial intelligence (AI) has, in one form or another, been in existence for over six decades. However, recent years have seen an enormous increase in the amount of collectable data and major advancements in algorithms and computer hardware. Within the realm of AI technology, machine learning (ML) and deep learning (DL) applications in particular have undergone significant growth Keras, one of the most popular DL frameworks, can quickly describe a DL model, begin training it on data, and generate more data by modifying existing data...

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