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NLP Demystified 9: Automatically Finding Topics in Documents with Latent Dirichlet Allocation

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Comments NLP Demystified 9: Automatically Finding Topics in Documents with Latent Dirichlet Allocation

It's really amazing work of NLP Comment from : @varshapandey_daily_lifestyle

thx so much Comment from : @kevinoudelet

Nicely done, thanks! Comment from : @somerset006

This is the best course for understanding NLP! The author did a great job explaining concepts in detail, but there is a minor terminology issue I want to highlight to avoid confusion When the course refers to "vocabulary", it does not always mean just the individual words More accurately, in NLP the "vocabulary" is the set of unique tokens that occur in the text corpusbrbrTo elaborate:brbr1 By default, the vocabulary contains the unique unigrams (single words) in the corpusbr2 However, it can also include n-grams (sequences of multiple words) if we tokenize the text into n-grams rather than just unigramsbr3 Therefore, it is more precise to refer to the "tokens" rather than just the "vocabulary" The term "tokens" makes it clear we could be talking about either unigrams or n-grams, depending on the tokenization approach usedbr4 This vocabulary or token set is what forms the basis for representations like word embeddings, indexing documents, etcbrbrThat being said, using "tokens" is a more accurate general term than "vocabulary" when we want to refer to both potential unigrams and n-grams Just wanted to point out this terminology distinction to prevent any confusion down the line Comment from : @vipulmaheshwari2321

Great NLP lectures Subscribe your channel Comment from : @caiyu538

i was going through the notebook file and i cant download the cnn corpus file from gdrive its says access denied? Comment from : @prithimeenan

Btw, when running the colab in the cloud (I preferred to do it that way) I had two issues that could be easily fixed Do you accept PRs to correct them? Comment from : @youfripper

keep up the good work Comment from : @mahmoudreda1083

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