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@@ -48,7 +48,7 @@ Below examples include the intense usage of industry-hot frameworks (i.e. Pytorc
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#### Recommedation System - Collaborative Filtering
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[FastAI Implementation](https://github.com/hyunjoonbok/Python-Projects/blob/master/Pytorch/TabNet%20in%20Pytorch%20-%20New%20Solution%20to%20Tabular%20ML%20problems.ipynb) \
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[FastAI Implementation](https://github.com/hyunjoonbok/Python-Projects/blob/master/vanilla/Recommendation%20System%20-%20Matrix%20Factoization%20(Collaboratvie%20Filtering)%20in%20FastAI.ipynb) \
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[Surprise Library Implementation](https://github.com/hyunjoonbok/Python-Projects/blob/master/vanilla/Recommendation%20System%20-%20Matrix%20Factoization%20(Collaboratvie%20Filtering)%20using%20Surprise%20Library.ipynb)
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<p>
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Experiment with the MovieLens 100K Data to provide movie recommendations for users based on different settings (Item-based, user-based, etc)

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