Last Updated on January 5, 2022 by shibatau
The last link is added.
I. What do you learn?
Let’s learn how to do the Natural Language Processing tasks, tokenization, stemming and lemmatization using the spaCy library.
Learning from the articles:
II. Install spaCy on Google Colaboratory
Install spaCy 2.3.5 and you will get the same results as in the explanation here.
!pip install spacy==2.3.5
You can see all the scripts here:
III. Sample strings
- ‘Manchester United is looking to sign a forward for $90 million’
- “Manchester United isn’t looking to sign any forward.”
- ‘”They\’re leaving U.K. for U.S.A.”‘
- “Hello, I am non-vegetarian, email me the menu at firstname.lastname@example.org”
- ‘Manchester United is looking to sign Harry Kane for $90 million’
‘compute computer computed computing’
‘A letter has been written, asking him to be released’
‘Hello from Stackabuse. The site with the best Python Tutorials. What are you looking for?’
Creating Doc objects:
IV. Tokenize a document
You can tokenize a document and access the token attributes.
Show the part of speech and dependencies
You can also visualize the dependencies. You can learn more in my post.
You can visualize dependencies of words online here:
To be continued.