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AWS Certified Machine Learning Specialty: MLS-C01 Certification Guide

You're reading from  AWS Certified Machine Learning Specialty: MLS-C01 Certification Guide

Product type Book
Published in Mar 2021
Publisher Packt
ISBN-13 9781800569003
Pages 338 pages
Edition 1st Edition
Languages
Authors (2):
Somanath Nanda Somanath Nanda
Profile icon Somanath Nanda
Weslley Moura Weslley Moura
Profile icon Weslley Moura
View More author details

Table of Contents (14) Chapters

Preface Section 1: Introduction to Machine Learning
Chapter 1: Machine Learning Fundamentals Chapter 2: AWS Application Services for AI/ML Section 2: Data Engineering and Exploratory Data Analysis
Chapter 3: Data Preparation and Transformation Chapter 4: Understanding and Visualizing Data Chapter 5: AWS Services for Data Storing Chapter 6: AWS Services for Data Processing Section 3: Data Modeling
Chapter 7: Applying Machine Learning Algorithms Chapter 8: Evaluating and Optimizing Models Chapter 9: Amazon SageMaker Modeling Other Books You May Enjoy

Processing real-time data using Kinesis data streams

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

  • Kinesis can be ingested by multiple producers and multiple consumers can also read data from the stream. Let's understand this by means of an example in real time. Suppose you have a producer ingesting data to a Kinesis stream and the default retention period is 24 hours, which means the 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, this should be consumed before it expires or can be stored somewhere if it's critical. The retention period can be extended to a maximum of 365 days at an extra...
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