Recommendation system based on content type I am new to this field and would like to know that for what kind of data types other than images, recommendation system can be created using machine learning. Suppose for contents like audio or video, is it necessary to use data set of actual audio files or video files or just text information about the file is enough for this system ?
Recommendation systems can be applied for anything, as long as you have sufficient training data.

The most important inputs to the recommendation system are not "audio files or video files".

Wikipedia gives you the list:


Similarity matrix
Item attributes
User activities and behaviours
User profile



  https://en.wikipedia.org/wiki/Recommender_system