Picture 1 of 1
Gallery
Picture 1 of 1
Have one to sell?
Joshua Arvin Lat Machine Learning Engineering on AWS (Paperback) (UK IMPORT)
US $90.78
ApproximatelyS$ 116.51
Condition:
Brand New
A new, unread, unused book in perfect condition with no missing or damaged pages.
More than 10 available
Oops! Looks like we're having trouble connecting to our server.
Refresh your browser window to try again.
Shipping:
Free Standard Shipping from outside US.
Located in: Rushden, United Kingdom
Delivery:
Estimated between Wed, 15 Oct and Fri, 24 Oct to 94104
Returns:
30 days return. Buyer pays for return shipping. If you use an eBay shipping label, it will be deducted from your refund amount.
Coverage:
Read item description or contact seller for details. See all detailsSee all details on coverage
(Not eligible for eBay purchase protection programmes)
Seller assumes all responsibility for this listing.
eBay item number:116772605068
Item specifics
- Condition
- Brand New: A new, unread, unused book in perfect condition with no missing or damaged pages. See all condition definitionsopens in a new window or tab
- Book Title
- Machine Learning Engineering on AWS
- Title
- Machine Learning Engineering on AWS
- Subtitle
- Build, scale, and secure machine learning systems and MLOps pipel
- EAN
- 9781803247595
- ISBN
- 9781803247595
- Release Date
- 04/22/2022
- Release Year
- 2022
- Country/Region of Manufacture
- GB
- Genre
- Computing & Internet
- Item Height
- 93mm
- Item Length
- 75mm
About this product
Product Identifiers
Publisher
Packt Publishing, The Limited
ISBN-10
1803247592
ISBN-13
9781803247595
eBay Product ID (ePID)
11058364131
Product Key Features
Subject
Systems Architecture / Distributed Systems & Computing, Data Modeling & Design, Image Processing, General
Publication Year
2022
Number of Pages
530 Pages
Language
English
Publication Name
Machine Learning Engineering on AWS : Build, Scale, and Secure Machine Learning Systems and MLOps Pipelines in Production
Type
Textbook
Subject Area
Computers, Science
Format
Trade Paperback
Additional Product Features
Dewey Edition
23
Dewey Decimal
006.31
Synopsis
Work seamlessly with production-ready machine learning systems and pipelines on AWS by addressing key pain points encountered in the ML life cycle Key Features: Gain practical knowledge of managing ML workloads on AWS using Amazon SageMaker, Amazon EKS, and more Use container and serverless services to solve a variety of ML engineering requirements Design, build, and secure automated MLOps pipelines and workflows on AWS Book Description: There is a growing need for professionals with experience in working on machine learning (ML) engineering requirements as well as those with knowledge of automating complex MLOps pipelines in the cloud. This book explores a variety of AWS services, such as Amazon Elastic Kubernetes Service, AWS Glue, AWS Lambda, Amazon Redshift, and AWS Lake Formation, which ML practitioners can leverage to meet various data engineering and ML engineering requirements in production. This machine learning book covers the essential concepts as well as step-by-step instructions that are designed to help you get a solid understanding of how to manage and secure ML workloads in the cloud. As you progress through the chapters, you'll discover how to use several container and serverless solutions when training and deploying TensorFlow and PyTorch deep learning models on AWS. You'll also delve into proven cost optimization techniques as well as data privacy and model privacy preservation strategies in detail as you explore best practices when using each AWS. By the end of this AWS book, you'll be able to build, scale, and secure your own ML systems and pipelines, which will give you the experience and confidence needed to architect custom solutions using a variety of AWS services for ML engineering requirements. What You Will Learn: Find out how to train and deploy TensorFlow and PyTorch models on AWS Use containers and serverless services for ML engineering requirements Discover how to set up a serverless data warehouse and data lake on AWS Build automated end-to-end MLOps pipelines using a variety of services Use AWS Glue DataBrew and SageMaker Data Wrangler for data engineering Explore different solutions for deploying deep learning models on AWS Apply cost optimization techniques to ML environments and systems Preserve data privacy and model privacy using a variety of techniques Who this book is for: This book is for machine learning engineers, data scientists, and AWS cloud engineers interested in working on production data engineering, machine learning engineering, and MLOps requirements using a variety of AWS services such as Amazon EC2, Amazon Elastic Kubernetes Service (EKS), Amazon SageMaker, AWS Glue, Amazon Redshift, AWS Lake Formation, and AWS Lambda -- all you need is an AWS account to get started. Prior knowledge of AWS, machine learning, and the Python programming language will help you to grasp the concepts covered in this book more effectively.
LC Classification Number
Q325.5
Item description from the seller
Seller business information
VAT number: GB 864154811
Seller feedback (788,988)
- a***9 (2701)- Feedback left by buyer.Past monthVerified purchaseA+
- 0***d (172)- Feedback left by buyer.Past monthVerified purchasetks for a great item loved putting it together.
- i***w (12)- Feedback left by buyer.Past monthVerified purchaseGreat show! Prompt delivery, even coming from UK! I specifically bought an ALL-REGIONS player so I could watch this. The cost of my new Blu-Ray player made up for the price difference between this item and a U.S. friendly one from Amazon!!! Now, I can watch any region DVD too.
Seller feedback (788,988)
- a***9 (2701)- Feedback left by buyer.Past monthVerified purchaseA+
- 0***d (172)- Feedback left by buyer.Past monthVerified purchasetks for a great item loved putting it together.
- i***w (12)- Feedback left by buyer.Past monthVerified purchaseGreat show! Prompt delivery, even coming from UK! I specifically bought an ALL-REGIONS player so I could watch this. The cost of my new Blu-Ray player made up for the price difference between this item and a U.S. friendly one from Amazon!!! Now, I can watch any region DVD too.