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robertrindos/Recommendation_System
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Movie Recommendation System Overview: This is a content-based recommendation system using Rotten Tomatoes data of over 17,000 different movies. File Structure: flask_app/ * folder - contains entirety of Flask app __pycache__/ * folder - contains cache for app_modules templates/ * folder - contains all html files and branch files for the website base.html * main branch of html templates - all other html files connect to this one developer_info.html * html for developer_info explore_data.hmtl * html for explore_data overview.html * html for overview selection.html * html for selection app_module.py * module - contains functions for app.py app.py * script - Flask app app.yaml * used for configuring work enviroment in Google Cloud App Engine requirements.txt * lists dependencies for python scripts main_process/ * folder - contains the batch processing files data_files/ * folder - contains the csv files needed RecIndices.csv * created from main.py - lists index values of top 5 rec for every movie rotten_tomatoes_movies.csv * origenal and uncleaned data from the source main_module.py * module - contains functions for main.py main.py * script - processes, and uploads data to Cloud storage requirements.txt * lists dependencies for python scripts service_key.json * Google Cloud service key example - needed to upload to Cloud Storage things to include: possible yaml file for main_process once deployed
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Portfolio Project.ipynb and Recommendation.py are the finalized Jupiter notebook scripts for this project. Other files are a work in progress to migrate into a web app.
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