https://github.com/prakashjha1/movie-recommendation-system

A recommendation system is a subclass of Information filtering Systems that seeks to predict the rating or the preference a user might give to an item. In simple words, it is an algorithm that suggests relevant items to users. Eg: In the case of Netflix which movie to watch, In the case of e-commerce which product to buy, or In the case of kindle which book to read, etc. I have used content based filtering which is one of the type of recommendation system.
https://github.com/prakashjha1/movie-recommendation-system

Last synced: 2 days ago
JSON representation

A recommendation system is a subclass of Information filtering Systems that seeks to predict the rating or the preference a user might give to an item. In simple words, it is an algorithm that suggests relevant items to users. Eg: In the case of Netflix which movie to watch, In the case of e-commerce which product to buy, or In the case of kindle which book to read, etc. I have used content based filtering which is one of the type of recommendation system.

• Host: GitHub
• URL: https://github.com/prakashjha1/movie-recommendation-system
• Owner: prakashjha1
• Created: 2022-04-12T05:27:24.000Z (over 2 years ago)
• Default Branch: main
• Last Pushed: 2022-04-12T07:16:26.000Z (over 2 years ago)
• Last Synced: 2023-09-16T10:42:23.526Z (about 1 year ago)
• Language: Jupyter Notebook
• Size: 8.67 MB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

README

        
# Movie-Recommendation-System

A recommendation system is a subclass of Information filtering Systems that seeks to predict the rating or the preference a user might give to an item. In simple words, it is an algorithm that suggests relevant items to users. Eg: In the case of Netflix which movie to watch, In the case of e-commerce which product to buy, or In the case of kindle which book to read, etc. I have used content based filtering which is one of the type of recommendation system.

# Steps to create this Movie Recommendation sytem

1. Import required libraries.

2. choose important columns from the dataset which can help in recommendation.

3. apply some operations on the columns like convert strings into lowercase, remove spaces, convert string into list etc.

4. combine all columns except movies title and make columns called tags.

5. use Countvectorizer 

6. use cosine similary to predict or recommend movies based on the selected movie

7. I have used streamlit to create front end.

I have created this project to learn and practice something.