Inspiration
Too many junk comments on the Internet
What it does
Detects the spam comments on youtube and masks them
How I built it
We pulled the training and testing data from UCR. We cleaned the data with a python pipeline with lowering alphabetical letters, stripping the HTML and email addresses, congregate numbers, detected dollar signs.
We used a support vector machine with Gaussian kernel. The final accuracy we get is 86.48%.
Challenges I ran into
Figured out the meaningful features. Cleaned up the data with regular expression.
Accomplishments that I'm proud of
Finished building the entire data processing pipeline and model production.
What I learned
Collaboration in between a full stack project.
What's next for direHusky
Finish up the chrome extension part. Publish online. Potentially optimize the model to have a better accuracy. Can also be applied to other Internet scenarios.
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