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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 The ultimate guide to passing the MLS-C01 exam on your first attempt

Product type Paperback

Published in Feb 2024

Publisher Packt

ISBN-13 9781835082201

Length 342 pages

Edition 2nd Edition

Languages

Python

Tools

AWS

Concepts

Machine Learning

Authors (2):

Somanath Nanda

Weslley Moura

View More author details

Table of Contents (13) Chapters

Preface

1. Chapter 1: Machine Learning Fundamentals FREE CHAPTER

2. Chapter 2: AWS Services for Data Storage

3. Chapter 3: AWS Services for Data Migration and Processing

4. Chapter 4: Data Preparation and Transformation

5. Chapter 5: Data Understanding and Visualization

6. Chapter 6: Applying Machine Learning Algorithms

7. Chapter 7: Evaluating and Optimizing Models

8. Chapter 8: AWS Application Services for AI/ML

9. Chapter 9: Amazon SageMaker Modeling

10. Chapter 10: Model Deployment

11. Chapter 11: Accessing the Online Practice Resources

12. Other Books You May Enjoy

Storing columnar data on Amazon Redshift

Amazon Redshift is not used for real-time transactions, but it is used for data warehouse purposes. It is designed to support huge volumes of data at a petabyte scale. It is a column-based database used for analytics, long-term processing, tending, and aggregation. Redshift Spectrum can be used to query data on S3 without loading data to the Redshift cluster (a Redshift cluster is required, though). It’s not an OLTP, but an OLAP. AWS QuickSight can be integrated with Redshift for visualization, with a SQL-like interface that allows you to connect using JDBC/ODBC connections to query the data.

Redshift uses a clustered architecture in one AZ in a VPC with faster network connectivity between the nodes. It is not high availability by design as it is tightly coupled to the AZ. A Redshift cluster has a leader node, and this node is responsible for all the communication between the client and the computing nodes of the cluster, query planning...

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Authors (2)

Nanda

Nanda

Somanath has 10 years of working experience in IT industry which includes Prod development, Devops, Design and architect products from end to end. He has also worked at AWS as a Big Data Engineer for about 2 years.

See other products by Nanda

Moura

Moura

Weslley Moura has been developing data products for the past decade. At his recent roles, he has been influencing data strategy and leading data teams into the urban logistics and blockchain industries.

See other products by Moura

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