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

Processing stored data on AWS

There are several services for processing the data stored in AWS. We will go through AWS Batch and AWS EMR (Elastic MapReduce) in this section. EMR is a product from AWS that primarily runs MapReduce jobs and Spark applications in a managed way. AWS Batch is used for long-running, compute-heavy workloads.


EMR is a managed implementation of Apache Hadoop provided as a service by AWS. It includes other components of the Hadoop ecosystem, such as Spark, HBase, Flink, Presto, Hive, Pig, and many more. We will not cover these in detail for the certification exam:

  • EMR clusters can be launched from the AWS console or via the AWS CLI with a specific number of nodes. The cluster can be a long-term cluster or an ad hoc cluster. If you have a long-running traditional cluster, then you have to configure the machines and manage them yourself. If you have jobs to be executed faster, then you need to manually add a cluster. In the case of EMR, these...