When using the scikit-learn library in Python, I can use the CountVectorizer to create ngrams of a desired length (e.g. 2 words) like so: from sklearn.metrics.
katacoda
crecordset
livewires
overhead
primeng-turbotable
azure-ase
chisel
nuget
git-fetch
google-nearby-connections
office-ui-fabric
content-negotiation
stack-navigator
kernighan-and-ritchie
jquery-datatables
bep20
ksql-datagen
tnsnames
r-inla
intel-cloud
windows-10-universal
jsr
canoe
picamera
autodiscovery
explicit-conversion
go-map
explicit-implementation
jstree
node-commander