The Definitive Guide to Machine Learning Operations in AWS: Machine Learning Scalability and Optimization with AWS - Image 1

£47.10

Apress The Definitive Guide to Machine Learning Operations in AWS: Machine Learning Scalability and Optimization with AWS

Name: The Definitive Guide to Machine Learning Operations in AWS: Machine Learning Scalability and Optimization with AWS
Brand: Apress
Price: 47.1 GBP
Availability: InStock

Managers' Guides to Computing

About as cheap as it gets. The only time it was cheaper was 2 months ago.

£47 today · all-time low £47 (Apr 2026) · usually £47

NEW HERE?

Amazon shows you one price. We show you all of them.

Tosheroon watches Amazon prices so you don't have to. Every product on Amazon has a price history — we make it visible. Set the price you'd actually pay, and we'll email you the second it gets there. No app, no account, one email.

WHAT'S ON THIS PAGE

↓ Price chart
when this has been cheap or pricey

↓ Forecast
where the price is heading next

↓ Statistics
all-time high & low, recent range

↑ Price alert
name your number, we'll email you

Price History & Forecast

Grey patches = out of stock. Cheaper = lower on the chart. Hover for exact prices.

Last 71 days · 71 data points (no recent data)

Historical

Generating forecast…

Price Distribution

Price distribution over 71 days • 2 price levels

Days at Price

Current Price

Price Analysis

Most common price: £47 (66 days, 93.0%)

Price range: £47 - £50

Price levels: 2 different prices over 71 days

Description

Foreword by Dr. Shreyas Subramanian, Principal Data Scientist, Amazon This book focuses on deploying, testing, monitoring, and automating ML systems in production. It covers AWS MLOps tools like Amazon SageMaker, Data Wrangler, and AWS Feature Store, along with best practices for operating ML systems on AWS. This book explains how to design, develop, and deploy ML workloads at scale using AWS cloud's well-architected pillars. It starts with an introduction to AWS services and MLOps tools, setting up the MLOps environment. It covers operational excellence, including CI/CD pipelines and Infrastructure as code. Security in MLOps, data privacy, IAM, and reliability with automated testing are discussed. Performance efficiency and cost optimization, like Right-sizing ML resources, are explored. The book concludes with MLOps best practices, MLOPS for GenAI, emerging trends, and future developments in MLOps By the end, readers will learn operating ML workloads on the AWS cloud. This book suits software developers, ML engineers, DevOps engineers, architects, and team leaders aspiring to be MLOps professionals on AWS. What you will learn: ● Create repeatable training workflows to accelerate model development ● Catalog ML artifacts centrally for model reproducibility and governance ● Integrate ML workflows with CI/CD pipelines for faster time to production ● Continuously monitor data and models in production to maintain quality ● Optimize model deployment for performance and cost Who this book is for: This book suits ML engineers, DevOps engineers, software developers, architects, and team leaders aspiring to be MLOps professionals on AWS.

Product Specifications

Brand: Apress
Format: paperback
ASIN: B0DGKDTPBF
Category: Books > Subjects > Business, Finance & Law > E-Commerce > Managers' Guides to Computing
Domain: Amazon UK
Release Date: 04 January 2025
Listed Since: 10 September 2024

Barcode

No barcode data available

Apress The Definitive Guide to Machine Learning Operations in AWS: Machine Learning Scalability and Optimization with AWS

About as cheap as it gets. The only time it was cheaper was 2 months ago.

Price History & Forecast

Price Distribution

Price Analysis

Description

Product Specifications

Barcode

Similar Products You Might Like

Practical MLOps: Operationalizing Machine Learning Models

The Machine Learning Solutions Architect Handbook: Create machine learning platforms to run solutions in an enterprise setting

MLOps with Ray: Best Practices and Strategies for Adopting Machine Learning Operations

Managing AI in the Enterprise: Succeeding with AI Projects and MLOps to Build Sustainable AI Organizations

Enterprise AI in the Cloud: A Practical Guide to Deploying End-to-End Machine Learning and ChatGPT Solutions (Tech Today)

AWS Certified Machine Learning Study Guide: Specialty (MLS-C01) Exam

Implementing MLOps in the Enterprise: A Production-First Approach

Practical Machine Learning with AWS: Process, Build, Deploy, and Productionize Your Models Using AWS

Manning Engineering Deep Learning Systems - Software Guide

Machine Learning in Production: From Models to Products

Platform and Model Design for Responsible AI: Design and build resilient, private, fair, and transparent machine learning models

AWS Certified Machine Learning Engineer Study Guide: Associate (MLA-C01) Exam (Sybex Study Guide)

Machine Learning Production Systems: Engineering Machine Learning Models and Pipelines

Official Google Cloud Certified Professional Machine Learning Engineer Study Guide (Sybex Study Guide)

AWS Certified Machine Learning Specialty: MLS-C01 Certification Guide: The definitive guide to passing the MLS-C01 exam on the very first attempt

A Complete Guide to DevOps with AWS: Deploy, Build, and Scale Services with AWS Tools and Techniques

Scalable AI and Design Patterns: Design, Develop, and Deploy Scalable AI Solutions

GenAI on AWS: A Practical Approach to Building Generative AI Applications on AWS (Tech Today)

MLOps Engineering at Scale: Deploying Pytorch Models on Aws

Deep Learning at Scale: At the Intersection of Hardware, Software, and Data

Introducing MLOps: How to Scale Machine Learning in the Enterprise

MIT Press Artificial Intelligence - A Systems Engineering Approach

Reaching Cloud Velocity - Second Edition: A Leader's Guide to Success in the AWS Cloud

Systematic Cloud Migration: A Hands-On Guide to Architecture, Design, and Technical Implementation