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Movie_Recommendartion

In this repo we implement a demo for movie recommendation.
We're working on getting the majority of those systems here and it will be a good resource for study purposes.
Feel free to fork the repository and make it for any other product recommendation needs

Demo

here is the web app

visualization

Running locally

use conda env(recommended)

  • using environment.yml
conda env create -f environment.yml
conda activate movie_recommendation_env
streamlit run movie_recommender.py
  • using requirements.txt
conda create --name env_name python==3.8
conda activate env_name
conda install --file requirements.txt
streamlit run movie_recommender.py

Resources

Blogs

  1. https://towardsdatascience.com/introduction-to-recommender-systems-6c66cf15ada
  2. https://pub.towardsai.net/recommendation-system-in-depth-tutorial-with-python-for-netflix-using-collaborative-filtering-533ff8a0e444
  3. https://medium.com/quantyca/deep-learning-for-collaborative-filtering-using-fastai-b28e197ccd59
  4. https://medium.com/the-owl/recommender-systems-f62ad843f70c
  5. https://towardsdatascience.com/collaborative-filtering-and-embeddings-part-1-63b00b9739ce
  6. https://towardsdatascience.com/various-implementations-of-collaborative-filtering-100385c6dfe0
  7. https://medium.com/hackernoon/introduction-to-recommender-system-part-1-collaborative-filtering-singular-value-decomposition-44c9659c5e75
  8. https://towardsdatascience.com/introduction-to-recommender-system-part-2-adoption-of-neural-network-831972c4cbf7
  9. https://towardsdatascience.com/various-implementations-of-collaborative-filtering-100385c6dfe0

Notebooks

  1. https://www.kaggle.com/ibtesama/getting-started-with-a-movie-recommendation-system
  2. https://www.kaggle.com/laowingkin/netflix-movie-recommendation
  3. https://www.kaggle.com/rounakbanik/movie-recommender-systems
  4. https://www.kaggle.com/kanncaa1/recommendation-systems-tutorial

Data

  1. https://grouplens.org/datasets/movielens/
  2. https://www.kaggle.com/tmdb/tmdb-movie-metadata?select=tmdb_5000_movies.csv

Streamlit

  1. https://github.com/gouravdidwania/Movie-Recommendation-System
  2. https://github.com/pr-atha-m/Movie_recommendation_system
  3. https://github.com/Explore-AI/unsupervised-predict-streamlit-template
  4. https://github.com/Chandru-21/End-to-End-Movie-Recommendation-System-with-deployment-using-docker-and-kubernetes

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