Practical machine learning with AWS : process, build, deploy, and productionize your models using AWS
"Successfully build, tune, deploy, and productionize any machine learning model, and know how to automate the process from data processing to deployment. This book is divided into three parts. Part I introduces basic cloud concepts and terminologies related to AWS services such as S3, EC2, Iden...
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Médium: | E-kniha |
Jazyk: | angličtina |
Vydáno: |
New York :
Apress :
2021
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Žánr/forma: | příručky elektronické knihy |
ISBN: | 978-1-4842-6222-1 978-1-4842-6221-4 9781484262214 9781484262238 |
Témata: | |
On-line přístup: | Plný text |
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Obsah:
- Part I: Introduction to Amazon Web Services
- Chapter 1: Cloud Computing and AWS
- Chapter 2: AWS Pricing and Cost Management
- Chapter 3: Security in Amazon Web Services
- Part II: Machine Learning in AWS
- Chapter 4: Introduction to Machine Learning
- Chapter 5: Data Processing in AWS
- Chapter 6: Building and Deploying Models in SageMaker
- Chapter 7: Using CloudWatch in SageMaker
- Chapter 8: Running a Custom Algorithm in SageMaker
- Chapter 9: Making an End-to-End Pipeline in SageMaker
- Part III: Other AWS Services
- Chapter 10: Machine Learning Use Cases in AWS