You're reading from The Machine Learning Solutions Architect Handbook Create machine learning platforms to run solutions in an enterprise setting

Product type Paperback

Published in Jan 2022

Publisher Packt

ISBN-13 9781801072168

Length 442 pages

Edition 1st Edition

Languages

Python

Tools

TensorFlow

Concepts

Machine Learning

Author (1):

David Ping

Preface

1. Section 1: Solving Business Challenges with Machine Learning Solution Architecture

2. Chapter 1: Machine Learning and Machine Learning Solutions Architecture FREE CHAPTER

3. Chapter 2: Business Use Cases for Machine Learning

4. Section 2: The Science, Tools, and Infrastructure Platform for Machine Learning

5. Chapter 3: Machine Learning Algorithms

6. Chapter 4: Data Management for Machine Learning

7. Chapter 5: Open Source Machine Learning Libraries

8. Chapter 6: Kubernetes Container Orchestration Infrastructure Management

9. Section 3: Technical Architecture Design and Regulatory Considerations for Enterprise ML Platforms

10. Chapter 7: Open Source Machine Learning Platforms

11. Chapter 8: Building a Data Science Environment Using AWS ML Services

12. Chapter 9: Building an Enterprise ML Architecture with AWS ML Services

13. Chapter 10: Advanced ML Engineering

14. Chapter 11: ML Governance, Bias, Explainability, and Privacy

15. Chapter 12: Building ML Solutions with AWS AI Services

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Hands-on lab – running ML tasks using AI services

In this hands-on lab, you will perform a list of ML tasks using Rekognition, Comprehend, Textract, and Transcribe. Follow these steps to get started:

Launch the SageMaker Studio profile you created in Chapter 8, Building a Data Science Environment Using AWS ML Services. You will create and run new notebooks in this profile.
We need to provide the new notebooks with permission to access AI services. To do this, find the Studio execution role for the Studio environment and attach the AdministratorAccess IAM policy to it. We will use this policy for simplicity here. In a controlled environment, you would need to design a policy to provide the specific permissions needed to access different services.
Clone https://github.com/PacktPublishing/The-Machine-Learning-Solutions-Architect-Handbook into your Studio environment using the git clone https://github.com/PacktPublishing/The-Machine-Learning-Solutions-Architect...