You're reading from The Machine Learning Solutions Architect Handbook Practical strategies and best practices on the ML lifecycle, system design, MLOps, and generative AI

Product type Paperback

Published in Apr 2024

Publisher Packt

ISBN-13 9781805122500

Length 602 pages

Edition 2nd Edition

Languages

Python

Tools

MLOps

Concepts

Machine Learning

Author (1):

David Ping

View More author details

Table of Contents (19) Chapters

Preface

1. Navigating the ML Lifecycle with ML Solutions Architecture FREE CHAPTER

2. Exploring ML Business Use Cases

3. Exploring ML Algorithms

4. Data Management for ML

5. Exploring Open-Source ML Libraries

6. Kubernetes Container Orchestration Infrastructure Management

7. Open-Source ML Platforms

8. Building a Data Science Environment Using AWS ML Services

9. Designing an Enterprise ML Architecture with AWS ML Services

10. Advanced ML Engineering

11. Building ML Solutions with AWS AI Services

12. AI Risk Management

13. Bias, Explainability, Privacy, and Adversarial Attacks

14. Charting the Course of Your ML Journey

15. Navigating the Generative AI Project Lifecycle

16. Designing Generative AI Platforms and Solutions

17. Other Books You May Enjoy

18. Index

Hands-on – creating a Kubernetes infrastructure on AWS

In this section, you will create a Kubernetes environment using Amazon EKS, a managed Kubernetes environment on AWS, which makes it easier to set up a Kubernetes cluster. Let’s first look at the problem statement.

Problem statement

As an ML solutions architect, you have been tasked with evaluating Kubernetes as a potential infrastructure platform for building an ML platform for one business unit in your bank. You need to build a sandbox environment on AWS and demonstrate that you can deploy a Jupyter notebook as a containerized application for your data scientists to use.

Lab instruction

In this hands-on exercise, you are going to create a Kubernetes environment using Amazon EKS, which is a managed service for Kubernetes on AWS that creates and configures a Kubernetes cluster with both master and worker nodes automatically. EKS provisions and scales the control plane, including the API server and...