SKU: 41424588093

Implementing MLOps in the Enterprise

Sale price$931.50 Regular price$1035.00
Save 10%

Pay in installments of $258.75 with ShopPay, AfterPay and Klarna

Shipping Estimate
USA
  • USA
  • CAN

Ships within 48 hours · Estimated delivery Jul 25 - Jul 30

Promo Codes Available:

For Your Every Summer RSVP, with Code: SUMMER15

Description

Implementing MLOps in the EnterpriseWith demand for scaling, real time access, and other capabilities, businesses need to consider building operational machine learning pipelines. This practical guide helps your company bring data science to life for different real world MLOps scenarios. Senior data scientists, MLOps engineers, and machine learning engineers will learn how to tackle challenges that prevent many businesses from moving ML models to production. Authors Yaron Haviv and Noah

With demand for scaling, real-time access, and other capabilities, businesses need to consider building operational machine learning pipelines. This practical guide helps your company bring data science to life for different real-world MLOps scenarios. Senior data scientists, MLOps engineers, and machine learning engineers will learn how to tackle challenges that prevent many businesses from moving ML models to production.Authors Yaron Haviv and Noah Gift take a production-first approach. Rather than beginning with the ML model, you'll learn how to design a continuous operational pipeline, while making sure that various components and practices can map into it. automating as many components as possible, and making the process fast and repeatable, your pipeline can scale to match your organization's needs.You'll learn how to provide rapid business value while answering dynamic MLOps requirements. This book will help you:
Learn the MLOps process, including its technological and business value
Build and structure effective MLOps pipelines
Efficiently scale MLOps across your organization• Explore common MLOps use cases
Build MLOps pipelines for hybrid deployments, real-time predictions, and composite AI
Learn how to prepare for and adapt to the future of MLOps
Effectively use pre-trained models like HuggingFace and OpenAI to complement your MLOps strategy
About the AuthorYaron Haviv is a serial entrepreneur who has been applying his deep technological experience in data, cloud, AI and networking to leading startups and enterprise companies since the late 1990s. As the co-founder and CTO of Iguazio, Yaron drives the strategy for the companys data science platform and leads the shift towards real- time AI. He also initiated and built Nuclio, a leading open source serverless platform with over 4,000 Github stars and MLRun, Iguazios open source MLOps orchestration framework.Noah Gift is the founder of Pragmatic A.I. Labs. Noah Gift 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, 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.

Shipping Notes
  • Free Standard Shipping on $100+ Orders to the USA.
  • Except Preorder products are shipped in 48 hours.
  • Delivery to the USA:
  1. Standard Shipping : 3-10 business days
  • If time is of the essence, please consider selecting expedited delivery for faster service.
Exchange/Return Notes
  • We offer a 30-day return/exchange service after receiving.
  • Final sale items are not eligible for returns or exchanges.
  • To process your return/exchange, please contact us at [email protected]
  • Please click here for more details>>> Return & Exchange Policy
SKU: 41424588093

Discover Niche Categories That Outsell

Top-Converting Item to Boost Your Average Order

4.2 ★★★★★
Based on 20 reviews
Sort
Highest Rating
Newest First
Oldest First
Product Reviews
A
Amazon customer
Port Orchard, US
★★★★★ 5
Great shoe well made
Size: 13 Little Kid, Color: Pink/Lavender, Size: 13 Little Kid, Color: Pink/Lavender
Really good shoes at a fair price. My daughter loves the pink and purple gradient colors. Really beautiful. Shoes have proven themselves very durable. She's been wearing these a few times a week for the last couple months and they still look new aside from some dirt stains. Fit perfectly. Very comfortable. This is always her first pick in the morning when she's getting dressed. Good breathability you can wear these in hot summer weather without sweaty feet. Versatile shoe looks good enough to wear out and about or exercise in.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on May 16, 2026
K
Verified Purchase
Kevin Keegan
Pawtucket, US
★★★★★ 3
Runs large
Size: 7 Big Kid, Color: White
Runs very large.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on June 5, 2026
L
Verified Purchase
Lou
Charlottesville, US
★★★★★ 5
a little roomy for narrow feet.
Size: 6 Big Kid, Color: Black/Black
Nice shoes. My little one has narrow feet so they are a little lose. Overall, a nice shoe.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on June 4, 2026
K
Verified Purchase
KNE
Lexington, US
★★★★★ 5
comfortable
Size: 7 Big Kid, Color: Black/Black
super comfortable!
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on May 30, 2026
M
Verified Purchase
Mike Summers
Houston, US
★★★★★ 5
Great shoes
Size: 5 Big Kid, Color: Navy/Blue
Loved them but bought a size too small so had to buy another pair…my bad 🤦🏽‍♀️
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on May 20, 2026

recommand products