In this project im trying to work myway around recommendation systems specifically using collaborative filtering

I use simple 100k movie ratings dataset .. in which i attached in the repo for purposes of replicating the same resuls

of course this can be upgraded to included other meta data and increase complexity

• Collaborative filtering is based on the fact that relationships exist between products and people’s interests. Many recommendation systems use collaborative filtering to find these relationships and to give an accurate recommendation of a product that the user might like or be interested in

• Collaborative filtering has basically two approaches: user-based and item-based. User-based collaborative filtering is based on the user similarity or neighborhood.