I used the dataset from Kaggle (https://www.kaggle.com/tmdb/tmdb-movie-metadata ). there are 2 csv files in the zip file. one of them is over 25 mb that's why couldn't upload it in the project folder.

This project was quite fun. I took help from several sites, Medium, towards data science, kaggle to complete this project. Thanks to these websites. Finally, this recommender version performed better than the previous version. I've used 2 methods of filtering for recommending movies, demographic and content based filtering. tried to implement collaborative filtering but it was a bit difficult.

collaborative filtering is much more popular nowadays but creating a model based on collaborative filtering was challenging. I'll probably try making one in the future.

If you are getting the message "Sorry, something went wrong. Reload?" message while opening the ipynb file, kindly checkout the following link

https://nbviewer.jupyter.org/github/faisalsanto007/movie-recommender-v2/blob/main/movie%20recommendation.ipynb