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.
tcp-ip
pdf.js.express
qlikview
get-filehash
netflix-dgs
amazon-swf
oracle-access-manager
aws-amplify-vue
declspec
object-literal
styled-system
django-3.2
mysql-error-1049
geofire
shopify-template
react-bootstrap-typeahead
speechsynthesizer
facebook-authentication
compose-spec
prism-7
flask-uploads
exclude
git-rev-list
acl
constructor-inheritance
tomcat-valve
des
grunt-contrib-compass
elevatr
asp.net-mvc-4