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data
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posters
posters
 
 
readmdasset
readmdasset
 
 
.gitattributes
.gitattributes
 
 
README.md
README.md
 
 
default-movie-poster.jpg
default-movie-poster.jpg
 
 
main_app.py
main_app.py
 
 
model building.ipynb
model building.ipynb
 
 
movie_list.csv
movie_list.csv
 
 
requirements.txt
requirements.txt
 
 
similarity.pkl
similarity.pkl
 
 
top_genres.csv
top_genres.csv
 
 
top_trend_mov.csv
top_trend_mov.csv
 
 
user_data.csv
user_data.csv
 
 
user_history_similarity.pkl
user_history_similarity.pkl
 
 

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Movie recommendation using Machine learning

ML Algorithm used : Cosine similarity

There are 4 sections in this project to showcase the recommendations

  1. Result Based on search. Alt text
  2. Result based on similarity. Alt text
  3. Result based on User watch history (Known as FOR YOU section). Alt text
  4. Top trending based on Genre among Populations watch. Alt text
  5. Top trending based on Title among population watch. Alt text

This is the Demo page:

visit website

Alt text

Take this project:

1. Clone the project and Install Streamlit using:

pip3 install streamlit or pip install streamlit

2. Run the app

streamlit run main_app.py

Boom Go! you are up!!!!

Note: All the file's data are available no need to search for anything Also if you want to make any changes in the code, use the notebook for experiments.

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Movie recommendation app uisng Python, streamlit and ML Algorithms

mov-rec.streamlit.app/

Topics

machine-learning ai project python3 cosine-similarity hacktoberfest movie-recommendation ml-project streamlit-webapp

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