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


In this chapter, we learned about a few of the AWS AI services that can be used to solve various problems. We used the Amazon Rekognition service, which detects objects and faces (including celebrity faces), and can also extract text from images. For text to speech, we used Amazon Polly, while for speech to text, we used Amazon Transcribe. Toward the end of this chapter, we built a chatbot in Amazon Lex.

For language detection and translation in an image, we used Amazon Rekognition, Amazon Comprehend, and Amazon Translate. We learned how to combine all of them into one Lambda function to solve our problem.

For the certification exam, you don't need to remember all the APIs we used in this chapter. There may be questions on a few of the best practices that we learned or on the names of services that solve a specific problem. It is always good to practice using these AWS AI services as it will enhance your architecting skills.

In the next chapter, we will learn...