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SageMaker-ready jupyter notebook for Machine Learning social media digestion.
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README.md
ml-fomo-sagemaker-notebook.ipynb

README.md

ML-Social-Network-Analysis-AWS-SageMaker

SageMaker-ready jupyter notebook for Machine Learning social media digestion.

Introduction

This is a production-ready notebook for training/running ML-fomo project on AWS SageMaker.

ML-fomo is an open source project for digesting/analysing twitter users' discussions about a certain topic.

Harnessing Machine Learning for classifying and estimating Twitter user's opinions and thoughts on a given topic.

Training/using models on a PC is time consuming, with AWS SageMaker we can train and use our model easily and it only takes a couple of seconds.

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Prerequisite

  • A minimal knowledge about Jupyter notebooks and AWS is required
  • AWS account

Getting Started

  1. Setup your AWS SageMaker account
  2. From your console, create a new notebook instance
  3. Make sure that your instance is inService then click "open jupyter"
  4. Clone this project and upload the ml-fomo-sagemaker-notebook.ipynb file to your instance.

LICENSE

This software is GPL licensed. The work based off of it must be released as open source.

This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.

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