https://github.com/rudrakshi99/movie-recommendation-system

Movie recommendation system using machine learning and predict user ratings for the movies.
https://github.com/rudrakshi99/movie-recommendation-system

dataframes machine-learning matplotlib numpy pandas seaborn

Last synced: 29 days ago
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Movie recommendation system using machine learning and predict user ratings for the movies.

• Host: GitHub
• URL: https://github.com/rudrakshi99/movie-recommendation-system
• Owner: rudrakshi99
• Created: 2021-07-22T16:55:47.000Z (over 3 years ago)
• Default Branch: master
• Last Pushed: 2021-07-22T17:08:11.000Z (over 3 years ago)
• Last Synced: 2024-11-22T05:34:12.585Z (3 months ago)
• Topics: dataframes, machine-learning, matplotlib, numpy, pandas, seaborn
• Language: Jupyter Notebook
• Homepage:
• Size: 2.82 MB
• Stars: 1
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Movie-Recommendation-System

Movie Recommendation System for the MovieLens Dataset using machine Learning and predict user ratings for Movies.

Python Libraries used:

* Pandas

* Numpy

* Matplotlib

* Seaborn

## Data Collection :

The dataset has been obtained from Grouplens.

Link : https://grouplens.org/datasets/movielens/20m/

This dataset (ml-20m) describes 5-star rating and free-text tagging activity from MovieLens, a movie recommendation service. It contains 20000263 ratings and 465564 tag applications across 27278 movies. These data were created by 138493 users between January 09, 1995 and March 31, 2015. This dataset was generated on October 17, 2016.

Users were selected at random for inclusion. All selected users had rated at least 20 movies. No demographic information is included. Each user is represented by an id, and no other information is provided.

For our objective, we would be using "u.data" and "u.item" data files.