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AWS Certified Machine Learning - Specialty (MLS-C01) Certification Guide

You're reading from AWS Certified Machine Learning - Specialty (MLS-C01) Certification Guide The ultimate guide to passing the MLS-C01 exam on your first attempt

Product type Paperback

Published in Feb 2024

Publisher Packt

ISBN-13 9781835082201

Length 342 pages

Edition 2nd Edition

Languages

Python

Tools

AWS

Concepts

Machine Learning

Authors (2):

Somanath Nanda

Weslley Moura

View More author details

Table of Contents (13) Chapters

Preface

1. Chapter 1: Machine Learning Fundamentals FREE CHAPTER

2. Chapter 2: AWS Services for Data Storage

3. Chapter 3: AWS Services for Data Migration and Processing

4. Chapter 4: Data Preparation and Transformation

5. Chapter 5: Data Understanding and Visualization

6. Chapter 6: Applying Machine Learning Algorithms

7. Chapter 7: Evaluating and Optimizing Models

8. Chapter 8: AWS Application Services for AI/ML

9. Chapter 9: Amazon SageMaker Modeling

10. Chapter 10: Model Deployment

11. Chapter 11: Accessing the Online Practice Resources

12. Other Books You May Enjoy

AWS Application Services for AI/ML

In this chapter, you will learn about the AWS AI services for building chatbots, advanced text analysis, document analysis, transcription, and so on. This chapter has been designed in such a way that you can solve different use cases by integrating AWS AI services and get an idea of how they work. AWS is growing every day, and they are adding new AI services regularly.

In this chapter, you will approach different use cases programmatically or from the console. This will help you understand different APIs and how to use them. You will use S3 for storage and AWS Lambda to execute any code. The examples in this chapter are in Python, but you can use other supported languages such as Java, Node.js, .NET, PowerShell, Ruby, and so on.

You will cover the following topics:

Analyzing images and videos with Amazon Rekognition
Text to speech with Amazon Polly
Speech to text with Amazon Transcribe
Implementing natural language processing...

The rest of the chapter is locked

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Authors (2)

Nanda

Nanda

Somanath has 10 years of working experience in IT industry which includes Prod development, Devops, Design and architect products from end to end. He has also worked at AWS as a Big Data Engineer for about 2 years.

See other products by Nanda

Moura

Moura

Weslley Moura has been developing data products for the past decade. At his recent roles, he has been influencing data strategy and leading data teams into the urban logistics and blockchain industries.

See other products by Moura

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