RecSys

This repo is used typical Recommend system.

The recommendation system are consist of following contents:

Knowledge-Based Recommendation 1.1 Used Data are three variables: timeline, genre and duration 1.2 Used Data are three variables: timeline, genre and duration 1.3
Content-Based Recommendation These are consist of two diffrent types of recommendations. The first is Plot description-based recommendation. Here are used the following data: the descriptions and taglines of diffrerent movies. The second is Metadata-based recommendation. Here are used the following data: genres, keywords, cast, and crew.
Building Collaborative Filters Here are used the MovieLens dataet ,which are well known and the most popular benchmark datasets. The used folders are following files: u.data, u.user and u.item. These varibles are movieId, movietitle, releasedate, videoreleasedate, IMDbURL, unkonwn and grenes are floowing: Action, Adventure, and ohters.

Requirements are written in requirements files. $ pip install -r requirements.txt

Name		Name	Last commit message	Last commit date
Latest commit History 17 Commits
.github/workflows		.github/workflows
7_Deep_Learning		7_Deep_Learning
1_data_munging.ipynb		1_data_munging.ipynb
2_Simple_Recommender.ipynb		2_Simple_Recommender.ipynb
3_Knowledge_Recommender.ipynb		3_Knowledge_Recommender.ipynb
4_Content_Based_Recommenders_ongoing.ipynb		4_Content_Based_Recommenders_ongoing.ipynb
4_Content_Based_Recommenders_ongoing_ipynb_のコピー.ipynb		4_Content_Based_Recommenders_ongoing_ipynb_のコピー.ipynb
6_Hybrid_Recommender.ipynb		6_Hybrid_Recommender.ipynb
README.md		README.md
requirements.txt		requirements.txt
simper_rec.ipynb		simper_rec.ipynb
simple_rec.ipynb		simple_rec.ipynb

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