Accelerate deep learning workloads with amazon sagemaker : train, deploy, and scale deep learning models effectively using amazon sagemaker [E-Book] / Vadim Dabravolski.
Over the past 10 years, deep learning has grown from being an academic research field to seeing wide-scale adoption across multiple industries. Deep learning models demonstrate excellent results on a wide range of practical tasks, underpinning emerging fields such as virtual assistants, autonomous d...
Saved in:
Full text |
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Personal Name(s): | Dabravolski, Vadim, author |
Imprint: |
Packt Publishing,
2022
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Physical Description: |
1 online resource (278 pages) |
Note: |
englisch |
ISBN: |
9781801813112 9781801816441 |
Keywords: |
Computers -- Business & Productivity Software -- General Computers -- Artificial Intelligence -- Natural Language Processing |
- Accelerate deep learning workloads with amazon sagemaker : train, deploy, and scale deep learning models effectively using amazon sagemaker
- Contributors
- Table of Contents
- Preface
- Part 1: Introduction to Deep Learning on Amazon SageMaker
- Chapter 1: Introducing Deep Learning with Amazon SageMaker
- Chapter 2: Deep Learning Frameworks and Containers on SageMaker
- Chapter 3: Managing SageMaker Development Environment
- Chapter 4: Managing Deep Learning Datasets
- Part 2: Building and Training Deep Learning Models
- Chapter 5: Considering Hardware for Deep Learning Training
- Chapter 6: Engineering Distributed Training
- Chapter 7: Operationalizing Deep Learning Training
- Part 3: Serving Deep Learning Models
- Chapter 8: Considering Hardware for Inference
- Chapter 9: Implementing Model Servers
- Chapter 10: Operationalizing Inference Workloads
- Index
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