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  • Book Overview & Buying AWS Certified Machine Learning - Specialty (MLS-C01) Certification Guide
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AWS Certified Machine Learning - Specialty (MLS-C01) Certification Guide

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

By : Somanath Nanda, Weslley Moura
4.6 (22)
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AWS Certified Machine Learning - Specialty (MLS-C01) Certification Guide

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

4.6 (22)
By: Somanath Nanda, Weslley Moura

Overview of this book

The AWS Certified Machine Learning Specialty (MLS-C01) exam evaluates your ability to execute machine learning tasks on AWS infrastructure. This comprehensive book aligns with the latest exam syllabus, offering practical examples to support your real-world machine learning projects on AWS. Additionally, you'll get lifetime access to supplementary online resources, including mock exams with exam-like timers, detailed solutions, interactive flashcards, and invaluable exam tips, all accessible across various devices—PCs, tablets, and smartphones. Throughout the book, you’ll learn data preparation techniques for machine learning, covering diverse methods for data manipulation and transformation across different variable types. Addressing challenges such as missing data and outliers, the book guides you through an array of machine learning tasks including classification, regression, clustering, forecasting, anomaly detection, text mining, and image processing, accompanied by requisite machine learning algorithms essential for exam success. The book helps you master the deployment of models in production environments and their subsequent monitoring. Equipped with insights from this book and the accompanying mock exams, you'll be fully prepared to achieve the AWS MLS-C01 certification.
Table of Contents (13 chapters)
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AWS Services for Data Migration and Processing

In the previous chapter, you learned about several ways of storing data in AWS. In this chapter, you will explore the techniques for using that data and gaining some insight from the data. There are use cases where you have to process your data or load the data to a hive data warehouse to query and analyze the data. If you are on AWS and your data is in S3, then you have to create a table in hive on AWS EMR to query the data in the hive table. To provide the same functionality as a managed service, AWS has a product called Athena, where you create a data catalog and query your data on S3. If you need to transform the data, then AWS Glue is the best option to transform and restore it to S3. Imagine a use case where you need to stream data and create analytical reports on that data. For this, you can opt for AWS Kinesis Data Streams to stream data and store it in S3. Using Glue, the same data can be copied to Redshift for further analytical...

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