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Natural Language Processing with spaCy & Python - Course for Beginners

Natural Language Processing with spaCy & Python - Course for Beginners

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Rating: 4.0; Vote: 1
In this spaCy tutorial, you will learn all about natural language processing and how to apply it to real-world problems using the Python spaCy library. - Course website with code: http://spacy.pythonhumanities.com/ -- Course developed by Dr. William Mattingly. https://www.youtube.com/pythontutorialsfordigitalhumanities
Date: 2022-03-14

Comments and reviews: 9


hi guys, great tutorial! Thanks for sharing it with us. I am not sure why this is happening but on the morphological analysis, the token2.morph gives a type error: TypeError: __repr__ returned non-string (type list), anyone can explain to me why this is happening? I am using google colab, thank you in advance
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I-ve come back to this video several times. The ONLY tutorial I-ve seen which walks through the whole process . The Python Tutorials for the digital humanities videos are also great. I am focused on biomedical text, but text is text when you are trying to get started.
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So I want ask a question about similarity. If I want to compare tow sentences like -I like apples.- and -I don't like apples- . They are different meanings , but the similarity is so high. How to avoid the situation that is too high similarity ?
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Everyone seemed to be asking for part 2, but this coverage is good enough - so good that I don't think it deserved a part 2, otherwise a large part is going to be lots of repetition. I will keep exploring deeper based on this video itself.
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Awesome content there Dr. William. I was really hyped during the series and every aspects of spaCy you've described perfectly. Now I'm interested on ML aspect of spaCY and It'd be great if you come with ML aspect of spaCy.
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Thank you for this fantastic video. Here's one question from vscode user. display.render(doc2, style='dep') has no reaction. I tried to find solutions on stack overflow but failed. Anyone can help? Many thanks.
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Thank you very much for making this video. I want to create my own corpus to analyze data. But as a newbie to Python, I found it really hard to start without a clear direction. Looking forward to Part 2!
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What should I do if I have a long text and I want to find a word like Denver Broncos and I want to know the four most similar words to it, like say Carolina Panthers or Jaguars or some other team?
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Thanks for sharing this enlighting stuff about the spaCy framework! Is there a date when you're gonna publish part 2? Can't wait to learn about the machine learning applications of spaCy.
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