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D-Lab's 12 hour introduction to text analysis with Python. Learn how to perform bag-of-words, sentiment analysis, topic modeling, word embeddings, and more, using scikit-learn, NLTK, Gensim, and spaCy...

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In Preprocessing Day 1, when spacy is imported on datahub I get the error: ImportError: cannot import name util

Topic Modeling is lesson number 4 but it is taught as the 3rd workshop in the series, whereas Word Embedding is lesson number 3 but it is taught as the...

I still get a warning when I run the code but some students got an actual error. This is the code that returns the error: nmf = NMF( n_components=n_components, random_state=random_state,...

Code that generates error: tfidf = vectorizer.fit_transform(data) tokens = vectorizer.get_feature_names_out() Error: Attribute Error: tfidfvectorizer does not have attribute 'get_feature_names_out'

This link in the text points to the generic datahub, so please update the link, as well as change the text to **D-Lab Datahub** instead of just **Datahub**: https://github.com/dlab-berkeley/Python-Text-Analysis/blob/111c54898a03c07207a7b831ee1705ee3449a468/README.md?plain=1#L89