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Update README.md
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README.md
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@@ -33,7 +33,7 @@ Meme folder consist of 222 meme images and Not Meme folder consist of 108 non me
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* Further work on the sentiment of the meme image like positive, voilence, offensive, sarcasm, neutral, etc. This can be used for various task like:
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* **Education** - To eliminate the offensive content from the curated memes for education
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* **Brand Monitoring** - To understand the sentiments of the user by understanding the representation by meme culture for decision making process.
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# Model Trained Using AutoTrain
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- Problem type: Binary Classification
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* Further work on the sentiment of the meme image like positive, voilence, offensive, sarcasm, neutral, etc. This can be used for various task like:
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* **Education** - To eliminate the offensive content from the curated memes for education
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* **Brand Monitoring** - To understand the sentiments of the user by understanding the representation by meme culture for decision making process.
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# Model Trained Using AutoTrain
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- Problem type: Binary Classification
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