Text Mining Basics in Python

[@Gorzkun]

This is amazing, well structured and right to the point in the explanation, thanks. I am really interested in Text mining and Text analytics, please I would love to see more about it.

[@Wawasabih]

Thanks for this wonderful video

[@mentalresilience]

Thank you for this video! I have a question: after setting the stopwords and looking at the filtered sentence (19:53) : why is the filtered sentence equal the tokenized sentence when the stopword list includes e.g. doing? Shouldn't it be deleted from the filtered sentence? An explaination would help me a lot. Thank you!

[@yasinortakc6170]

In the code tokenized-text should be replaced with tokenized_word. Then all stopwords can be removed.

[@mentalresilience]

@@yasinortakc6170 thank you!

[@cristopherespiritu4606]

I've been checking what I have this type of error. Hope you can help. TypeError Traceback (most recent call last) in () 6 7 word = "Working" ----> 8 print("Lemmatized Word: ", lem.lemmatize(word, "v")) 9 print("Stemmed Word: ", stem.stem(word)) 10 TypeError: 'tuple' object is not callable

[@Matin_2001]

🇮🇷❤️