Examples and best practices for building recommendation systems

hey one of the authors here. We are planning to create some notebooks on recommendation about recommendation algos :-)

thanks for the comment, would this definition be clearer: "Recall at k is the proportion of relevant items found in the top-k recommendations"?

It is also my sadness - AFAIK pyspark.ml does not support ranking metrics (does it?). So we wrapped the RDD and expose data frame as interfaces in our own implementations (the `reco_utils`). Implicit feedback is mentioned in a notebook under `staging` branch (https://github.com/Microsoft/Recommenders/blob/staging/noteb...). Will be there soon in the next release (1st of Feb)!