Implementation of algorithms in Python (recommendation algorithms)

Implement recommendation algorithms in Python in the form of a demonstration system (for example, using Jupyter notebooks).

We implement the selected recommendation algorithms (classical, as well as based on machine learning techniques) using libraries that are already ready for this (no need to reinvent the wheel).

For example: LightFM (hybrid recommendation system), Surprise(Collaborative Filtering), TensorFlow Recommender(Neural Collaborative Filtering), etc.

A given algorithm should make the appropriate recommendation on the provided data. (That is, in short, on the same data set we try to use different algorithms to be able to compare the results obtained).

I will provide more information on priv.