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96859891
MLOps Engineering at Scale (Paperback)
Item #:
96859891
NAD 1273
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MLOps Engineering at Scale shows you how to put machine learning into production efficiently by using pre-built services from AWS and other cloud vendors.
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What Stands Out
Comprehensive Guide
Offers extensive coverage of MLOps principles, frameworks, and tools, providing readers with in-depth knowledge crucial for implementing machine learning operations effectively at scale.
Practical Techniques
Equips practitioners with actionable strategies and real-world case studies, ensuring readers can apply concepts effectively and overcome common challenges in the deployment of machine learning models.
Expert Insights
Authored by industry experts, it delivers authoritative perspectives and best practices, making it an essential reference for both beginners and experienced professionals in MLOps.
Product Details
| Book format | Paperback |
| Fiction/nonfiction | Non-Fiction |
| Genre | Nonfiction |
| Publication date | March, 2022 |
| Pages | 250 |
| Reading level | General |
| Subgenre | Computers/Data Science - Machine Learning |
| Edition | Paperback |
| Publisher | Pearson Education |
| Original languages | English |
| Language | English |
| Edu focus | Engineering |
| Awards won | three corporate technology awards from IBM |
| Digital file format | PDF, Kindle, ePub |
| Digital reader format | PDF, Kindle, and ePub |
| Digital audio file format | PDF, Kindle, and ePub |
| Retail packaging | Single Piece |
| Assembled product height | 9.21 in |
| Assembled product weight | 1.25 lb (570 grams) |
| Bisac subject heading | Computers |
Who Should Buy?
-
Data Scientists
Provides essential MLOps practices enabling data scientists to collaborate effectively in deploying machine learning models.
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Machine Learning Engineers
Offers in-depth methodologies for engineers to streamline workflows, enhance productivity, and manage complex models efficiently.
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Team Leads
Equips team leads with the knowledge to oversee teams implementing scalable MLOps solutions within organizations.
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Beginners
May be too advanced for individuals new to machine learning or MLOps concepts without prior experience.
Product Description
MLOps Engineering at Scale (Paperback)
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Carl Osipov All Books Editorial Review
MLOps Engineering at Scale (Paperback) offers a comprehensive exploration of MLOps principles, ideal for those looking to deepen their understanding of machine learning operations. This non-fiction work, published by Pearson Education in March 2022, spans 250 pages and is written in English. The book is designed for general readers interested in the engineering aspect of computing, providing a valuable resource in modern data practices. Its digital formats, including PDF, Kindle, and ePub, ensure accessibility for various reading preferences, making it a versatile addition to any tech enthusiast's library.
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Pros
- Accessible in multiple digital formats
- In-depth exploration of MLOps principles
- Suitable for general readers
- Well-structured for easy comprehension
- Published by a reputable provider
Cons
- May be too technical for beginners
Product Price History
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Features & Benefits
- Dodge costly infrastructure tasks with MLOps.
- Rapidly bring machine learning models to production.
- Learn to deploy model training pipelines as service endpoints.
- Use AWS and cloud services to reduce development time.
- Includes a free eBook with your purchase.
- Ideal for Python and SQL users, no cloud experience needed.
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