物品 #:
238684559
MLOps Engineering at Scale: Deploying Pytorch Models on Aws
物品 #:
238684559
HKD 668
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現在訂購，約可在下列時間收貨： 星期四, 十一月 05
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MLOps Engineering at Scale teaches you how to implement efficient machine learning systems using pre-built services from AWS and other cloud vendors.
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What Stands Out
Scalable Deployment
Effortlessly deploy PyTorch models at any scale on AWS, ensuring that your machine learning applications can handle increased loads and complex data demands efficiently.
Integrated Solutions
Leverage AWS services seamlessly with PyTorch, providing a streamlined workflow for model training, optimization, and deployment that enhances productivity and reduces operational overhead.
Optimized Performance
Maximize your model performance with advanced AWS infrastructure, tailored for PyTorch, enabling faster inference and improved resource management for enterprise-level applications.
產品詳情
- Learn how to rapidly bring machine learning models to production with MLOps and pre-built serverless tools
- Gain knowledge in extracting, transforming, and loading datasets
- Understand the concept of automatic differentiation in PyTorch
- Deploy model training pipelines as a service endpoint
- Learn to monitor and manage the lifecycle of your ML pipeline
- Implement efficient machine learning systems using pre-built services from AWS and other cloud vendors
| Publisher | Manning Publications |
| Publication date | 1 Mar. 2022 |
| Edition | 1st |
| Language | English |
| Print length | 250 pages |
| ISBN-10 | 1617297763 |
| ISBN-13 | 978-1617297762 |
| Dimensions | 18.73 x 1.78 x 23.5 cm |
產品敘述
MLOps Engineering at Scale: Deploying Pytorch Models on Aws
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English edition Carl Osipov Format: Paperback Editorial Review
MLOps Engineering At Scale: Deploying Pytorch Models On Aws, published by Manning Publications, is a comprehensive guide that delves into the intricacies of deploying data models effectively. With 250 pages of insightful content, readers can expect to deepen their understanding of MLOps practices tailored for PyTorch on AWS. The book is written in English and is structured to cater to engineers looking to enhance their deployment skills. It offers both theoretical knowledge and practical approaches to streamline your ML workflow in a cloud environment.
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優點
- Comprehensive coverage of MLOps topics
- Practical approaches for deploying models
- Well-structured content for engineers
- Focus on PyTorch and AWS integration
- Suitable for both beginners and experienced users
缺點
- Might require additional resources for deep dives
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HKD 668
現在訂購，約可在下列時間收貨： 星期四, 十一月 05
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特色和優勢
- Learn how to rapidly create flexible and scalable machine learning systems without taking on the costly overhead of physical hardware.
- Master how to deploy model training pipelines as a service endpoint, monitor and manage your pipeline’s life cycle and measure performance improvements.
- No cloud experience is required to understand and implement the concepts mentioned in the book.
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