As a Data, we had the honor of analyzing the data for @TECHFESTSULI this year. Our team diligently cleaned and analyzed the data to gather insights on the visitors' demographics, satisfaction rates, top projects, and even provided suggestions for improvement.
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These comments, which are short pieces of text, were categorized as either positive (medical) or negative (non-medical) for the purpose of text classification. The negative comments make up 55% of the dataset, while the positive comments make up 45%.
Medical and Non-medical Short Textes Over Social Media
The dataset was created by using the Facebook app to gather comments from users.
https://t.co/k4nyd9lyPK
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As the progress in machine learning and artificial intelligence gaining more momentum, we felt the need to have a data collection repository that is specialized for Kurdish data.
https://t.co/WNZgXmU2yH
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