https://github.com/shimaa83/recommendation_system
recommendation system using different technique for netflix dataset
https://github.com/shimaa83/recommendation_system
kaggle-dataset knn-algorithm machine-learning recommendation-system
Last synced: about 1 month ago
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recommendation system using different technique for netflix dataset
- Host: GitHub
- URL: https://github.com/shimaa83/recommendation_system
- Owner: shimaa83
- Created: 2022-08-24T19:18:33.000Z (over 3 years ago)
- Default Branch: main
- Last Pushed: 2022-11-13T08:05:15.000Z (about 3 years ago)
- Last Synced: 2025-01-20T04:34:46.186Z (about 1 year ago)
- Topics: kaggle-dataset, knn-algorithm, machine-learning, recommendation-system
- Language: Jupyter Notebook
- Homepage:
- Size: 81.1 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# Recommendation System
- in this Repo we try to use the following type of recommendation systems
- Content-based recommenders
- Collaborative filtering :
1. memory based filter:
- item based filter
- user based filter
2. model based filter using KNN model
- make function that takes an input of any customer id and it return back what should be recommended for him
- make function that take movie name and it give back top 10 related movies.
# Dataset
using netflix data set https://www.kaggle.com/datasets/netflix-inc/netflix-prize-data
downlaoaded from kaggel to google colab using python code