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


  1. You are working as a data scientist for a healthcare company and are creating a machine learning model to predict fraud, waste, and abuse across the company's claims. One of the features of this model is the number of times a particular drug has been prescribed, to the same patient of the claim, in a period of 2 years. Which type of feature is this?

    a) Discrete

    b) Continuous

    c) Nominal

    d) Ordinal


    a, The feature is counting the number of times that a particular drug has been prescribed. Individual and countable items are classified as discrete data.

  2. You are building a ML model for an educational group that owns schools and universities across the globe. Your model aims to predict how likely a particular student is to leave his/her studies. Many factors may contribute to school dropout, but one of your features is the current academic stage of each student: preschool, elementary school, middle school, or high school. Which type of feature is this?

    a) Discrete...