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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 : Nanda, 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: Nanda, 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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Processing real-time data using Kinesis Data Streams

Kinesis is Amazon’s streaming service and can be scaled based on requirements. It has a level of persistence that retains data for 24 hours by default or optionally up to 365 days. Kinesis Data Streams is used for large-scale data ingestion, analytics, and monitoring:

  • Kinesis streams can be ingested by multiple producers and multiple consumers can also read data from the streams. The following is an example to help you understand this. Suppose you have a producer ingesting data to a Kinesis stream and the default retention period is 24 hours, which means data ingested at 05:00:00 A.M. today will be available in the stream until 04:59:59 A.M. tomorrow. This data won’t be available beyond that point, and ideally, it should be consumed before it expires; otherwise, it can be stored somewhere if it’s critical. The retention period can be extended to a maximum of 365 days, at an extra cost.
  • Kinesis can...
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AWS Certified Machine Learning - Specialty (MLS-C01) Certification Guide
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