Python-Text-Analysis-Fundamentals
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dlab-berkeley
D-Lab's 9 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...
3 attendees at start of workshop. Challenge 1 in "Fit a logistic regression model" section - mistake in code - need to remove the df_bin; also had to adjust Challenge...
After using up 1 GB of memory on JupyterHub, the kernel fails. We are not sure of how to remove objects that currently exist in the Jupyter Notebook so that...
See detailed comment from https://github.com/dlab-berkeley/computational-text-analysis-spring-2019/pull/22 pull request.
Replace lda = LatentDirichletAllocation(n_topics=10, max_iter=20, random_state=0) with lda = LatentDirichletAllocation(n_components=10, max_iter=20, random_state=0) in 02-unsupervised.ipynb and 02-unupervised-solutions.ipynb for newer versions of sklearn?
Update print("Cosine similarity between first and second book:") cosine_similarity needs updating
What you'll learn: - Would it be better to drop the reference to cosine similarity here as an "unsupervised method" along the lines of tf-idf and topic modeling? - Would...
import nltk nltk.download('punkt')
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D-Lab's 9 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...