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Machine Learning on Kubernetes

You're reading from   Machine Learning on Kubernetes A practical handbook for building and using a complete open source machine learning platform on Kubernetes

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Product type Paperback
Published in Jun 2022
Publisher Packt
ISBN-13 9781803241807
Length 384 pages
Edition 1st Edition
Languages
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Authors (2):
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Ross Brigoli Ross Brigoli
Author Profile Icon Ross Brigoli
Ross Brigoli
Faisal Masood Faisal Masood
Author Profile Icon Faisal Masood
Faisal Masood
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Toc

Table of Contents (16) Chapters Close

Preface 1. Part 1: The Challenges of Adopting ML and Understanding MLOps (What and Why)
2. Chapter 1: Challenges in Machine Learning FREE CHAPTER 3. Chapter 2: Understanding MLOps 4. Chapter 3: Exploring Kubernetes 5. Part 2: The Building Blocks of an MLOps Platform and How to Build One on Kubernetes
6. Chapter 4: The Anatomy of a Machine Learning Platform 7. Chapter 5: Data Engineering 8. Chapter 6: Machine Learning Engineering 9. Chapter 7: Model Deployment and Automation 10. Part 3: How to Use the MLOps Platform and Build a Full End-to-End Project Using the New Platform
11. Chapter 8: Building a Complete ML Project Using the Platform 12. Chapter 9: Building Your Data Pipeline 13. Chapter 10: Building, Deploying, and Monitoring Your Model 14. Chapter 11: Machine Learning on Kubernetes 15. Other Books You May Enjoy

Introducing Apache Airflow

Apache Airflow is an open source software designed for programmatically authoring, executing, scheduling, and monitoring workflows. A workflow is a sequence of tasks that can include data pipelines, ML workflows, deployment pipelines, and even infrastructure tasks. It was developed by Airbnb as a workflow management system and was later open sourced as a project in Apache Software Foundation's incubation program.

While most workflow engines use XML to define workflows, Airflow uses Python as the core language for defining workflows. The tasks within the workflow are also written in Python.

Airflow has many features, but we will cover only the fundamental bits of Airflow in this book. This section is by no means a detailed guide for Airflow. Our focus is to introduce you to the software components for the ML platform. Let's start with DAG.

Understanding DAG

A workflow can be simply defined as a sequence of tasks. In Airflow, the sequence...

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