Recommendation-System

• Content Based filtering

• Collaborative based filtering

• Hybrid based filtering (Combination of both)

├── DATA
│       1) MovieLens-dataset-1 (Used in Basic Recommendation System.ipynb)
│           ├── users
│           ├── Item_Id_Titles
│       2) ml-latest-small (Used in "Recommendation System (Content Based).ipynb" and "Recommendation System (Collaborative Based).ipynb")
│           ├── links.csv
│           ├── movies.csv
│           ├── ratings.csv
│           ├── tags.csv
│       3) tmdb-dataset (Used in "Recommendation System using Weighted Hyrid .ipynb")
│           ├── tmdb_5000_credits.csv
│           ├── tmdb_5000_movies.csv
├── Notebook
│    ├── Basic Recommendation System.ipynb
|    ├── Recommendation System (Collaborative Based).ipynb
|    ├── Recommendation System (Content Based).ipynb
|    ├── Recommendation System using Weighted Hyrid .ipynb

• This project goal is to build a Recommendation System, a system based on content filtering and collaborative filtering using KNN and cosine similarity.
• End result will be a system that Recommend similar movies for the given movie.