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Learning Data Mining with Python, - Second Edition

You're reading from  Learning Data Mining with Python, - Second Edition

Product type Book
Published in Apr 2017
Publisher Packt
ISBN-13 9781787126787
Pages 358 pages
Edition 2nd Edition
Languages
Concepts

Table of Contents (20) Chapters

Title Page
Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface
Getting Started with Data Mining Classifying with scikit-learn Estimators Predicting Sports Winners with Decision Trees Recommending Movies Using Affinity Analysis Features and scikit-learn Transformers Social Media Insight using Naive Bayes Follow Recommendations Using Graph Mining Beating CAPTCHAs with Neural Networks Authorship Attribution Clustering News Articles Object Detection in Images using Deep Neural Networks Working with Big Data Next Steps...

Training on Amazon's EMR infrastructure


We are going to use Amazon's Elastic Map Reduce (EMR) infrastructure to run our parsing and model building jobs.

In order to do that, we first need to create a bucket in Amazon's storage cloud. To do this, open the Amazon S3 console in your web browser by going to http://console.aws.amazon.com/s3 and click on Create Bucket. Remember the name of the bucket, as we will need it later.

Right-click on the new bucket and select Properties. Then, change the permissions, granting everyone full access. This is not a good security practice in general, and I recommend that you change the access permissions after you complete this chapter. You can use advanced permissions in Amazon's services to give your script access and also protect against third parties viewing your data.

Left-click the bucket to open it and click on Create Folder. Name the folder blogs_train. We are going to upload our training data to this folder for processing on the cloud.

On your computer...

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