Book Image

AWS Certified Machine Learning Specialty: MLS-C01 Certification Guide

By : Somanath Nanda, Weslley Moura
Book Image

AWS Certified Machine Learning Specialty: MLS-C01 Certification Guide

By: Somanath Nanda, Weslley Moura

Overview of this book

The AWS Certified Machine Learning Specialty exam tests your competency to perform machine learning (ML) on AWS infrastructure. This book covers the entire exam syllabus using practical examples to help you with your real-world machine learning projects on AWS. Starting with an introduction to machine learning on AWS, you'll learn the fundamentals of machine learning and explore important AWS services for artificial intelligence (AI). You'll then see how to prepare data for machine learning and discover a wide variety of techniques for data manipulation and transformation for different types of variables. The book also shows you how to handle missing data and outliers and takes you through various machine learning tasks such as classification, regression, clustering, forecasting, anomaly detection, text mining, and image processing, along with the specific ML algorithms you need to know to pass the exam. Finally, you'll explore model evaluation, optimization, and deployment and get to grips with deploying models in a production environment and monitoring them. By the end of this book, you'll have gained knowledge of the key challenges in machine learning and the solutions that AWS has released for each of them, along with the tools, methods, and techniques commonly used in each domain of AWS ML.
Table of Contents (14 chapters)
Section 1: Introduction to Machine Learning
Section 2: Data Engineering and Exploratory Data Analysis
Section 3: Data Modeling

Chapter 2: AWS Application Services for AI/ML

In this chapter, we 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 their usages. We 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.

We are going to 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...