Shop Stickerbox
Buy New
To see product details, add this item to your cart.
Ships from: Amazon.com
Sold by: Amazon.com
To see product details, add this item to your cart. You can always remove it later.
Shipper / Seller
Amazon.com
Amazon.com
Shipper / Seller
Amazon.com
Returns
30-day refund / replacement
30-day refund / replacement
This item can be returned in its original condition for a full refund or replacement within 30 days of receipt.
Read full return policy
Support
Product support included
What's Product Support?
In the event your product doesn't work as expected or you need help using it, Amazon offers free product support options such as live phone/chat with an Amazon associate, manufacturer contact information, step-by-step troubleshooting guides, and help videos. By solving product issues, we help the planet by extending the life of products. Availability of support options differ by product and country. Learn more
Payment
Secure transaction
Your transaction is secure
We work hard to protect your security and privacy. Our payment security system encrypts your information during transmission. We don’t share your credit card details with third-party sellers, and we don’t sell your information to others. Learn more
Gift options
Available at checkout
Available at checkout This item is a gift. Change
At checkout, you can add a custom message, a gift receipt for easy returns and have the item gift-wrapped
To see product details, add this item to your cart. You can always remove it later.
Minimal or no signs of wear, writing, or notes. ~ BooksRun: cheaper books, every time! Minimal or no signs of wear, writing, or notes. ~ BooksRun: cheaper books, every time! See less
Access codes and supplements are not guaranteed with used items.
Ships from and sold by BooksRun.
Added to

Sorry, there was a problem.

There was an error retrieving your Wish Lists. Please try again.

Sorry, there was a problem.

List unavailable.
Kindle app logo image

Download the free Kindle app and start reading Kindle books instantly on your smartphone, tablet, or computer - no Kindle device required.

Read instantly on your browser with Kindle for Web.

Using your mobile phone camera - scan the code below and download the Kindle app.

QR code to download the Kindle App

  • Practical MLOps: Operationalizing Machine Learning Models

Follow the author

Get new release updates & improved recommendations
Noah Gift
Follow
Something went wrong. Please try your request again later.

Practical MLOps: Operationalizing Machine Learning Models

by Noah Gift (Author), Alfredo Deza (Author) Format: Paperback
4.0 out of 5 stars (61)

Purchase options and add-ons

Getting your models into production is the fundamental challenge of machine learning. MLOps offers a set of proven principles aimed at solving this problem in a reliable and automated way. This insightful guide takes you through what MLOps is (and how it differs from DevOps) and shows you how to put it into practice to operationalize your machine learning models.

Current and aspiring machine learning engineers--or anyone familiar with data science and Python--will build a foundation in MLOps tools and methods (along with AutoML and monitoring and logging), then learn how to implement them in AWS, Microsoft Azure, and Google Cloud. The faster you deliver a machine learning system that works, the faster you can focus on the business problems you're trying to crack. This book gives you a head start.

You'll discover how to:

  • Apply DevOps best practices to machine learning
  • Build production machine learning systems and maintain them
  • Monitor, instrument, load-test, and operationalize machine learning systems
  • Choose the correct MLOps tools for a given machine learning task
  • Run machine learning models on a variety of platforms and devices, including mobile phones and specialized hardware

Read more
Previous slide of product details
  1. ISBN-10
    1098103017
  2. ISBN-13
    978-1098103019
  3. Edition
    1st
  4. Publisher
    O'Reilly Media
  5. Publication date
    October 19, 2021
  6. Language
    English
  7. Dimensions
    6.75 x 1 x 8.75 inches
  8. Print length
    458 pages
Next slide of product details

Frequently bought together

This item: Practical MLOps: Operationalizing Machine Learning Models
$58.48
Get it as soon as Monday, Sep 21
In Stock
Ships from and sold by Amazon.com.
+
AI Engineering: Building Applications with Foundation Models
$52.40
Get it as soon as Monday, Sep 21
In Stock
Ships from and sold by Amazon.com.
+
Designing Machine Learning Systems: An Iterative Process for Production-Ready Applications
$40.00
Get it as soon as Monday, Sep 21
In Stock
Ships from and sold by Amazon.com.
Total price: $00
To see our price, add these items to your cart.
Details
Added to Cart
Choose items to buy together.

Customers also bought or read

Page 1 of 1Start over
Previous page
  4. Book cover Introducing MLOps: How to Scale Machine Learning in the Enterprise
    Introducing MLOps: How to Scale Machine Learning in the Enterprise
    Paperback
    $36.49
    FREE delivery Tue, Sep 22
  9. Book cover Mathematics for Machine Learning
    Mathematics for Machine Learning
    Paperback
    $51.44
    FREE delivery Tue, Sep 22
  11. Book cover Deep Learning (Adaptive Computation and Machine Learning series)
    Deep Learning (Adaptive Computation and Machine Learning series)
    Hardcover
    $51.51
    FREE delivery Tue, Sep 22
  12. Book cover Machine Learning System Design Interview
    Machine Learning System Design Interview
    Paperback
    $31.80
    Delivery Tue, Sep 22
  19. Book cover Fluent Python: Clear, Concise, and Effective Programming
    Fluent Python: Clear, Concise, and Effective Programming
    Paperback
    $43.99
    FREE delivery Mon, Sep 21
  25. Book cover Natural Language Processing with Transformers, Revised Edition
    Natural Language Processing with Transformers, Revised Edition
    Paperback
    $41.60
    FREE delivery Mon, Sep 21
  27. Book cover Generative AI System Design Interview
    Generative AI System Design Interview
    Paperback
    $34.93
    Delivery Tue, Sep 22
Next page
Loading...

From the brand

  2. Hands-On Machine Learning with Scikit-Learn and PyTorch: Concepts, Tools, and Techniques to Build...
    AI Engineering: Building Applications with Foundation Models
    An Illustrated Guide to AI Agents: Concepts and Code for Building Agents with LLMs, Tools, and Me...
    AI Agents: The Definitive Guide: Design, Deployment, and Evaluation for Production

    Machine Learning, AI & more

    Visit the Store

  3. Machine Learning Design Patterns: Solutions to Common Challenges in Data Preparation, Model Build...
    Designing Machine Learning Systems: An Iterative Process for Production-Ready Applications
    AI and Machine Learning for Coders: A Programmer's Guide to Artificial Intelligence
    Building Machine Learning Systems with a Feature Store: Batch, Real-Time, and LLM Systems

    Machine Learning

    Visit the Store

  4. AI Systems Performance Engineering: Optimizing Model Training and Inference Workloads with GPUs, ...
    Generative AI Design Patterns: Solutions to Common Challenges When Building GenAI Agents and Appl...
    Designing AI Interfaces: Design Principles for Creative and Autonomous AI
    Building AI-Powered Products: The Essential Guide to AI and GenAI Product Management

    Artificial Intelligence

    Visit the Store

  5. Fundamentals of Deep Learning: Designing Next-Generation Machine Intelligence Algorithms
    Deep Learning for Coders with Fastai and PyTorch: AI Applications Without a PhD
    Generative Deep Learning: Teaching Machines To Paint, Write, Compose, and Play
    Deep Learning from Scratch: Building with Python from First Principles

    Deep Learning

    Visit the Store

  6. Practical Natural Language Processing: A Comprehensive Guide to Building Real-World NLP Systems
    Prompt Engineering for LLMs: The Art and Science of Building Large Language Model–Based Applications
    Designing Large Language Model Applications: A Holistic Approach to LLMs
    Learning LangChain: Building AI and LLM Applications with LangChain and LangGraph

    Language Processing (NLP, LLM)

    Visit the Store

  7. Sharing the knowledge of experts

    O'Reilly's mission is to change the world by sharing the knowledge of innovators. For over 40 years, we've inspired companies and individuals to do new things (and do them better) by providing the skills and understanding that are necessary for success.

    Our customers are hungry to build the innovations that propel the world forward. And we help them do just that.

From the Publisher

Practical MLOps

How This Book Is Organized

We designed this book so that you can consume each chapter as a standalone section designed to give you immediate help. At the end of each chapter are discussion questions that are intended to spur critical thinking and technical exercises to improve your understanding of the material.

These discussion questions and exercises are also well suited for use in the classroom in a Data Science, Computer Science, or MBA program and for the motivated self-learner. The final chapter contains several case studies helpful in building a work portfolio as an expert in MLOps.

The book is divided into 12 chapters, which we’ll break down a little more in the following section. At the end of the book, there is an appendix with a collection of valuable resources for implementing MLOps.

Chapters

The first few chapters cover the theory and practice of both DevOps and MLOps. One of the items covered is how to set up continuous integration and continuous delivery. Another critical topic is Kaizen, i.e., the idea of continuous improvement in everything.

There are three chapters on cloud computing that cover AWS, Azure, and GCP. Alfredo, a developer advocate for Microsoft, is an ideal source of knowledge for MLOps on the Azure platform. Likewise, Noah has spent years getting students trained on cloud computing and working with the education arms of Google, AWS, and Azure. These chapters are an excellent way to get familiar with cloud-based MLOps.

Other chapters cover critical technical areas of MLOps, including AutoML, containers, edge computing, and model portability. These topics encompass many cutting-edge emerging technologies with active traction.

Finally, in the last chapter, Noah covers a real-world case study of his time at a social media startup and the challenges they faced doing MLOps.

Appendixes

The appendixes are a collection of essays, ideas, and valuable items that cropped up in years between finishing Python for DevOps (O’Reilly) and this book. The primary way to use them is to help you make decisions about the future.

Exercise Questions

In this book’s exercises, a helpful heuristic considers how you can leverage them into a portfolio using GitHub and a YouTube walkthrough of what you did. In keeping with the expression “a picture is worth a thousand words,” a YouTube link to a walkthrough of a reproducible GitHub project on a resume may be worth 10,000 words and puts the resume in a new category of qualification for a job.

Editorial Reviews

About the Author

Noah Gift is the founder of Pragmatic A.I. Labs. He lectures at MSDS, at Northwestern, Duke MIDS Graduate Data Science Program, the Graduate Data Science program at UC Berkeley, the UC Davis Graduate School of Management MSBA program, UNC Charlotte Data Science Initiative, and University of Tennessee (as part of the Tennessee Digital Jobs Factory). He teaches and designs graduate machine learning, MLOps, AI, and data science courses, and consulting on machine learning and cloud architecture for students and faculty. As a former CTO, individual contributor, and consultant he has over 20 years' experience shipping revenue-generating products in many industries including film, games, and SaaS.

Alfredo Deza is a passionate software engineer, speaker, author, and former Olympic athlete with almost two decades of DevOps and software engineering experience. He currently teaches Machine Learning Engineering and gives worldwide lectures about software development, personal development, and professional sports. Alfredo has written several books about DevOps and Python, and continues to share his knowledge about resilient infrastructure, testing, and robust development practices in courses, books, and presentations.

Product details

  • Publisher ‏ : ‎ O'Reilly Media
  • Publication date ‏ : ‎ October 19, 2021
  • Edition ‏ : ‎ 1st
  • Language ‏ : ‎ English
  • Print length ‏ : ‎ 458 pages
  • ISBN-10 ‏ : ‎ 1098103017
  • ISBN-13 ‏ : ‎ 978-1098103019
  • Item Weight ‏ : ‎ 2.31 pounds
  • Dimensions ‏ : ‎ 6.75 x 1 x 8.75 inches
  • Best Sellers Rank: #272,526 in Books (See Top 100 in Books)
  • Customer Reviews:
    4.0 out of 5 stars (61)

About the author

Follow authors to get new release updates, plus improved recommendations.
Noah Gift

Noah Gift

Brief content visible, double tap to read full content.
Full content visible, double tap to read brief content.

Noah Gift is the founder of Pragmatic AI Labs. Noah Gift lectures at MSDS, at Northwestern, Duke MIDS Graduate Data Science Program, and the Graduate Data Science program at UC Berkeley and the UC Davis Graduate School of Management MSBA program, and UNC Charlotte Data Science Initiative. He is teaching and designing graduate machine learning, A.I., Data Science courses, and consulting on Machine Learning and Cloud Architecture for students and faculty. These responsibilities include leading a multi-cloud certification initiative for students.

Noah is a Python Software Foundation Fellow, and AWS ML Hero. He currently holds the following industry certifications for AWS: AWS Subject Matter Expert (SME) on Machine Learning, AWS Certified Solutions Architect, and AWS Certified Machine Learning Specialist, AWS Certified Big Data Specialist, AWS Academy Accredited Instructor, AWS Faculty Ambassador. He also is certified on both the Google and Azure platform: Google Certified Professional Cloud Architect, Certified Microsoft MTA on Python. He has published over 100 technical publications including multiple books on subjects ranging from Cloud Machine Learning to DevOps. Publications appear in Forbes, IBM, Red Hat, Microsoft, O’Reilly, Pearson, Udacity, Coursera, datascience.com, and DataCamp. Workshops and Talks around the world for organizations including NASA, PayPal, PyCon, Strata, O’Reilly Software Architecture Conference, and FooCamp. As an SME on Machine Learning for AWS, he helped created the AWS Machine Learning certification.

He has worked in roles ranging from CTO, General Manager, Consulting CTO, Consulting Chief Data Scientist, and Cloud Architect. This experience has been with a wide variety of companies: ABC, Caltech, Sony Imageworks, Disney Feature Animation, Weta Digital, AT&T, Turner Studios, and Linden Lab, and industries: Television, Film, Games, SaaS, Sports, Telecommunications. He has film credits in many major motion pictures for technical work, including Avatar, Spider-Man 3, and Superman Returns.

He has been responsible for shipping many new products at multiple companies that generated millions of dollars of revenue and had a global scale. Currently, he is consulting startups and other companies, on Machine Learning, Cloud Architecture, and CTO level consulting as the founder of Pragmatic A.I. Labs.

Related books

Page 1 of 1Start Over
Sponsored
Previous page
  1. Shop the Store on Amazon ›
    Step-by-Step Electrical Engineering: Learn and Apply Core Concepts Quickly. Build Your Knowledge with Practical Examples - No Background Required! Perfect for Aspiring Engineers and Enthusiasts!
    Step-by-Step Electrical Engineering: Learn and Apply Core Concepts Quickly. Build Your Knowledge with Practical Examples - No Background Required! Perfect for Aspiring Engineers and Enthusiasts!
    4.54.5 out of 5 stars368
    $19.99
  2. Shop the Store on Amazon ›
    Python Programming for Beginners: The Complete Python Coding Crash Course - Boost Your Growth with an Innovative Ultra-Fast Learning Framework and Exclusive Hands-On Interactive Exercises & Projects
    Python Programming for Beginners: The Complete Python Coding Crash Course - Boost Your Growth with an Innovative Ultra-Fast Learning Framework and Exclusive Hands-On Interactive Exercises & Projects
    4.54.5 out of 5 stars1,011
    $24.90
  3. Shop the Store on Amazon ›
    ChatGPT AND GENERATIVE AI SIMPLIFIED: NAVIGATE ARTIFICIAL INTELLIGENCE WITH CONFIDENCE, CRAFT EFFECTIVE PROMPTS, BOOST WRITING CREATIVITY AND ENHANCE LEARNING & SKILL DEVELOPMENT
    ChatGPT AND GENERATIVE AI SIMPLIFIED: NAVIGATE ARTIFICIAL INTELLIGENCE WITH CONFIDENCE, CRAFT EFFECTIVE PROMPTS, BOOST WRITING CREATIVITY AND ENHANCE LEARNING & SKILL DEVELOPMENT
    4.74.7 out of 5 stars31
    $16.95
  4. Shop the Store on Amazon ›
    50 Algorithms Every Programmer Should Know: Tackle computer science challenges with classic to modern algorithms in machine learning, software design, data systems, and cryptography
    50 Algorithms Every Programmer Should Know: Tackle computer science challenges with classic to modern algorithms in machine learning, software design, data systems, and cryptography
    4.74.7 out of 5 stars118
    $33.77 List:$49.99
  5. Shop the Store on Amazon ›
    NMLS SAFE MLO Study Cards 2026-2027: NMLS Exam Prep and Practice Test Questions for Mortgage Loan Originators [Color-Coded]
    NMLS SAFE MLO Study Cards 2026-2027: NMLS Exam Prep and Practice Test Questions for Mortgage Loan Originators [Color-Coded]
    4.54.5 out of 5 stars31
    $38.19 List:$44.99
Next page