Browse 117 Natural Language Processing questions and answers from learners and industry experts. Find practical fixes, interview prep and step-by-step solutions - or ask your own.
Let us assume of the following data from sklearn.feature_extraction.text import TfidfVectorizer from sklearn.decomposition import TruncatedSVD X =…
1 Answer · 1.4K Views · Answered ✓
Word embeddings are basically a representation of text used to let a machine understand what a human being wants to convey and they are represented…
1 Answer · 1.1K Views · Answered ✓
Using gensim, we can get the number of words using. vocab field of the Word2Vec model's wv property, as a dictionary, with the keys being each token.…
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It is a process of extracting all information referring to the same entity present in the text. For example, in the sentence ‘I supported Mr. Holmes…
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Damerau- Levenshtein algorithm measures the string between two sequences. It basically involves three classical edit operations which are insertion,…
1 Answer · 1.6K Views · Answered ✓
To perform an LDA model, we need to import the following codeNow we will perform preprocessing to make the data ready
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Some of the algorithms commonly used for edit-distance phenomenon are- Longest Common Sequence or LCS Damerau-Levenshtein distance
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model = gensim.models.doc2vec.Doc2Vec(size= 100, min_count = 5,window=4, iter = 50, workers=cores) model.build_vocab(res) model.train(res,…
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My dataset is unlabeled. Below is the code class MySentences(object): def __init__(self, dirname): self.dirname = dirname def __iter__(self): for…
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It is a process of finding out the dissimilarity between two strings. It basically counts the minimum number of steps required for transformation of…
1 Answer · 1.5K Views · Answered ✓
Case1.Case2.This happens becaus
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CRF or Conditional Random Field is a graphical model based on probability that is used to predict by taking sequential data or patterns into account.…
1 Answer · 2.1K Views · Answered ✓
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