to be ignored
updated
simplify es communication
index the data
little helper
walk through data
Item model
get user data
nan, l2n, timespan ..
moved corpus to top level
model and query separated
query
transform the training data into internal structure
added recommendations
split train and test set
changed the algorithms for right input
augmented the utils
get rid of the es indexing ...it is useless
get first 1000 lines
get rid of the recom part and find nearests