E-book – Practical MLOps: Operationalizing Machine Learning Models 1st Edition, Kindle Edition (PDF Instant Download)
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Product details
ISBN-13: 978-1098102975
Author: Noah Gift, Alfredo Deza
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
Please note: This is an Ebook, not a Paper Book or Audio Book!
Delivery: This can be downloaded immediately after purchasing.
Version: Only PDF Version.
Compatible Devices: Can be read on any device (Kindle, NOOK, Android/IOS devices, Windows, MAC).
Quality: High Quality. No missing contents. Printable.
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