Machine Learning Engineering on AWS - Second Edition Build, deploy, and operationalize LLMs, AI agents, and generative AI systems on AWS
Language: English
Published by Packt Publishing, 2026
- Softcover
- New
Condition: New
£ 62.94
Quantity: 2 available
Add to basketItem description from seller
This hands-on book teaches you how to design, build, optimize, and secure generative AI systems and AI agents on AWS. As you progress through the chapters, you'll leverage various AWS services to automate end-to-end LLMOps pipelines. Sprache: Englisch Gewicht in Gramm: 1082.
Seller Inventory # IB-7329561
- Title
- Machine Learning Engineering on AWS - Second Edition Build, deploy, and operationalize LLMs, AI agents, and generative AI systems on AWS
- Author
- Joshua Arvin Lat
- Publisher
- Packt Publishing
- Publication year
- 2026
- Condition
- Neu
- Binding
- Softcover/Taschenbuch
- Language
- English
- ISBN 10
- 1835881084
- ISBN 13
- 9781835881088
- Item weight
- 1,082 grams
Solve machine learning engineering challenges for GenAI-powered systems and AI agents on AWS, and automate LLMOps pipelines using Amazon Bedrock, SageMaker AI, Bedrock AgentCore, and Strands Agents.
Free with your book: DRM-free PDF version + access to Packt's next-gen Reader*
Key Features
- Build and scale AI agents using Amazon Bedrock AgentCore and Strands Agents
- Fine-tune, evaluate, and deploy ML models using Amazon SageMaker AI
- Automate LLMOps workflows with SageMaker Pipelines
Book Description
Modern AI systems increasingly leverage large language models, retrieval-augmented generation, and AI agents to power generative AI applications in the cloud. As organizations operationalize these systems at scale, there is a growing need for engineers with strong machine learning engineering expertise. To stay ahead in this rapidly evolving field, you need a deep understanding of AI and ML concepts as well as, practical, hands-on experience with the platforms and tools used to build and operate production-grade AI systems.
Machine Learning Engineering on AWS is a practical guide that shows you how to use AWS services such as Amazon Bedrock and Amazon SageMaker AI to fine-tune, evaluate, and deploy LLMs and generative AI systems. You'll learn how to develop RAG-powered systems, build and deploy AI agents using Bedrock AgentCore and Strands Agents, evaluate models using LLM-as-a-judge techniques, and automate LLMOps pipelines using SageMaker Pipelines. The book also covers best practices for building scalable, secure, and production-ready GenAI systems.
AWS AI hero Joshua Arvin Lat equips you with the skills and practical knowledge to handle a wide variety of ML engineering requirements, helping you design, operationalize, and secure generative AI systems and AI agents on AWS with confidence.
*Email sign-up and proof of purchase required"
What you will learn
- Build and deploy AI agents using Bedrock AgentCore and Strands Agents
- Dive deep into ML engineering with Amazon SageMaker AI
- Evaluate model performance using LLM-as-a-judge
- Explore advanced model fine-tuning and deployment using SageMaker AI
- Build RAG-powered systems using Bedrock Knowledge Bases and S3 Vectors
- Modernize analytics with a managed transactional data lake
- Automate LLMOps pipelines using SageMaker Pipelines and AWS Lambda
- Explore best practices for building GenAI systems and AI agents on AWS
Who this book is for
This book is intended for AI engineers, data scientists, machine learning engineers, and technology leaders who want to deepen their understanding of machine learning engineering, generative AI, large language models, retrieval-augmented generation, AI agents, and MLOps on AWS. A foundational understanding of artificial intelligence, machine learning, generative AI, and cloud engineering concepts is recommended.
Table of Contents
- A Gentle Introduction to Generative AI and AI Agents on AWS
- Building AI Agents with SageMaker AI and Bedrock AgentCore
- Machine Learning Engineering with Amazon SageMaker AI
- Modernizing Analytics with a Managed Transactional Data Lake
- Practical Data Management on AWS
- Pragmatic Data Processing on AWS
- SageMaker AI Model Training and Tuning Capabilities
- SageMaker AI Model Deployment Options and Strategies
- Automating LLMOps Workflows with SageMaker Pipelines
"Synopsis" may belong to another edition of this title.
About the Author
Joshua Arvin Lat is the Chief Technology Officer (CTO) of NuWorks Interactive Labs, Inc. He previously served as the CTO for three Australian-owned companies and as director of software development and engineering for multiple e-commerce start-ups in the past. Years ago, he and his team won first place in a global cybersecurity competition with their published research paper. He is also an AWS Machine Learning Hero and has shared his knowledge at several international conferences, discussing practical strategies on machine learning, engineering, security, and management.
"About the title" may belong to another edition of this title.
Shipping rates from Germany to U.S.A.
| Item | 10 to 12 business days | 8 to 10 business days |
|---|---|---|
| First item | £ 50.56 | £ 76.10 |
Payment methods
- Check
Specialty
BuchRight of withdrawal
If you are a consumer you can withdraw from the contract in accordance with the following. Consumer means any natural person who is acting for purposes which are outside his trade, business, craft or profession.
Information regarding the right of withdrawal
Statutory right to withdraw
You have the right to withdraw from this contract within 14 days without giving any reason.
The withdrawal period will expire after 14 days from the day on which you acquire, or a third party other than the carrier and indicated by you acquires, physical possession of the last good or the last lot or piece.
To exercise the right of withdrawal, electronically fill in and submit a clear statement on our website, under "My Purchases" in "My Account". We will communicate to you an acknowledgement of receipt of such a withdrawal on a durable medium (e.g. by e-mail) without delay.
To meet the withdrawal deadline, it is sufficient for you to send your communication concerning your exercise of the right of withdrawal before the withdrawal period has expired.
Effects of withdrawal
If you withdraw from this contract, we will reimburse to you all payments received from you, including the costs of delivery (except for the supplementary costs arising if you chose a type of delivery other than the least expensive type of standard delivery offered by us).
We may make a deduction from the reimbursement for loss in value of any goods supplied, if the loss is the result of unnecessary handling by you.
We will make the reimbursement without undue delay, and not later than 14 days after the day on which we are informed about your decision to withdraw from this contract.
We will make the reimbursement using the same means of payment as you used for the initial transaction, unless you have expressly agreed otherwise; in any event, you will not incur any fees as a result of such reimbursement.
We may withhold reimbursement until we have received the goods back, or you have supplied evidence of having sent back the goods, whichever is the earliest.
You shall send back the goods or hand them over to Home-set, Mannheim, Germany, without undue delay and in any event not later than 14 days from the day on which you communicate your withdrawal from this contract to us. The deadline is met if you send back the goods before the period of 14 days has expired. You will have to bear the direct cost of returning the goods. You are only liable for any diminished value of the goods resulting from the handling other than what is necessary to establish the nature, characteristics and functioning of the goods.
Exceptions to the right of withdrawal
The right of withdrawal does not apply to:
- The delivery of newspapers, journals or magazines with the exception of subscription contracts; and
- The supply of digital content which is not supplied on a tangible medium (e.g. on a CD or DVD) if you accepted when you placed your order that we could start to deliver it, and that you could not withdraw once delivery had started.