This is a simple django project which has a well-working implementation of recommendation systems(content-based filtering and collaborative filtering) for an e-commerce application using python librabries: NumPy, Pandas, Sklearn
For content-based filtering, cosine_similarity has been used to find angular distance vector between products, which falls under sklearn library.
For collaborative-filtering, matrix factorization method has been used to find co-relation between matrices, which falls under NumPy, sklearn libraries.
It has a login portal from where it can distinguish users and recommends product according to their past histories and ratings.
It does have a clean user interface - everything on one page.
It is a simple application programmed using python + django and has django's default database sqlite. It stores user's search history and use it to recommend(content-based) products. It has a 'Rating' model which stores user-product-rating data to recommend(collaborative) products. It also recommend products on popularity based filtering which is nothing but the count of products with maximum orders.
--------------------------------------Happy coding!!🍀-----------------------------------------------------