Chinmayrane16/Recommender-Systems-with-Collaborative-Filtering-and-Deep-Learning-Techniques
Implemented User Based and Item based Recommendation System along with state of the art Deep Learning Techniques
This helps e-commerce managers, content strategists, or product owners suggest relevant items to their users. It takes past user interactions with products or content (like movie ratings) and outputs personalized recommendations, helping improve user engagement and sales. This is for anyone looking to implement or understand how recommendation engines work.
No commits in the last 6 months.
Use this if you need to understand or build systems that recommend products, movies, articles, or other items to users based on their past behavior or similar users' preferences.
Not ideal if you need a recommendation system for extremely large datasets requiring advanced hybrid or dimensionality reduction techniques out-of-the-box.
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Jupyter Notebook
License
MIT
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Last pushed
Jul 20, 2020
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