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Effective Amazon Machine Learning

You're reading from   Effective Amazon Machine Learning Expert web services for machine learning on cloud

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Product type Paperback
Published in Apr 2017
Publisher Packt
ISBN-13 9781785883231
Length 306 pages
Edition 1st Edition
Languages
Tools
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Author (1):
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 Perrier Perrier
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Perrier
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Table of Contents (17) Chapters Close

Title Page
Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Dedication
Preface
1. Introduction to Machine Learning and Predictive Analytics FREE CHAPTER 2. Machine Learning Definitions and Concepts 3. Overview of an Amazon Machine Learning Workflow 4. Loading and Preparing the Dataset 5. Model Creation 6. Predictions and Performances 7. Command Line and SDK 8. Creating Datasources from Redshift 9. Building a Streaming Data Analysis Pipeline

Summary


In the first part of this chapter, we went through the Amazon account creation and how to properly set up and secure access to your AWS account. Using a combination of Multi Factor Authentication and User creation, we were able to quickly reach a satisfactory level of safety. AWS is a powerful platform with powerful tools and it's important to implement the best access protection possible.

In the second part, we went through the different steps involved in a simple linear regression prediction, from loading the data into S3, making that data accessible to Amazon ML via datasources, creating models, interpreting evaluations, and making predictions on new data.

The Amazon ML flow is smooth and facilitates the inherent data science loop: data, model, evaluation, and prediction.

In the following chapter, we will dive further into data preparation and data transformation. This time we will use a classic binary classification problem, namely, survival on the Titanic, which is based on a very...

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