A machine learning movie recommendation system using collaborative filtering.
Project contributor: Abhimanyu Santani Algorithm used: Collaborative Filtering
The data-set was taken from kaggle.com and the copy of the data set is present in the repo.
The recommendation system recommends the movies which have a higher correlation with the movie which you want to compare and the number of people has been set to 100 for comparison.
I have used Python's inbuilt numpy and panda's library to use the inbuilt functions. I have also used Python's matplotlib and seaborn to do a data-analysis. Python's panda dataframe has been used to clean data. I have used two movies "Return of the Jedi" and "Toy Story" to print all the movies which have similar correlation with it using inbuilt Python's library. The code has been throughly explained by comment lines at every step.