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.
salesforce-service-cloud
jtag
react-d3
productbuild
schemaspy
itcl
date-arithmetic
xna-4.0
window-decoration
constantcontact
erlang-stdlib
rspec
fulfillment
workload-scheduler
pitch
demographics
apple-app-site-associate
cakephp-2.2
android-min-sdk
ada
doskey
tinyalsa
swagger-core
notifications
evaporate.js
array-reduce
firemonkey
alphabetic
sld-resolution
ebay-net-sdk