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.
natural-join
automator
twincat-ads-.net
noexcept
python-collections
spring-jdbc
code-composer
aka.ms
cglib
user-data
facebook-instant-games
maxscale
pssnapin
compcert
bluetooth-lowenergy
ttl
stream-graph
testcafe
prism-7
erlang-shell
datatemplate
ember-power-select
patricia-trie
dmx512
.net-standard-1.4
akka-camel
smp
parchment
base62
google-cloud-spanner-emulator