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DimitriKourouniotis authored Aug 28, 2018
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Expand Up @@ -8,7 +8,7 @@ In the winter of 2017 there were numerous articles about quantity of fake commen

A blog post published by Jeff Kao caught my attention and I followed up with him on his analysis of the text. He provided me with the unedited 22 million filings available. I analyzed a sample of 3 million of them to see what I could find to develop my own features based around the text of faked comments.

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<a href="https://github.com/DimitriKourouniotis/Capstone1FCCNN/blob/master/Capstone%201%20Report%20FCC%20Net%20Neutrality%20Submissions.pdf">Capstone Report (pdf)</a>

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<a href="https://github.com/DimitriKourouniotis/Capstone1FCCNN/blob/master/08%20Capstone%201%20Stats%20Proportions%20by%20State%20relative%20to%20Population.ipynb">08 Statistics Proportions by State Relative to Population</a>

<a href="https://github.com/DimitriKourouniotis/Capstone1FCCNN/blob/master/09%20Classifiers%20and%20Feature%20Selections.ipynb">09 Classifiers and Feature Selection</a>
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## Acknowledgements


Many thanks to my mentor, Rajiv Shah!

### Thanks to the following for the data and code help for this capstone:<br>
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