Top "Gensim" questions

Gensim is a free Python framework designed to automatically extract semantic topics from documents, as efficiently (computer-wise) and painlessly (human-wise) as possible.

How to calculate the sentence similarity using word2vec model of gensim with python

According to the Gensim Word2Vec, I can use the word2vec model in gensim package to calculate the similarity …

python gensim word2vec
How to create a word cloud from a corpus in Python?

From Creating a subset of words from a corpus in R, the answerer can easily convert a term-document matrix into …

python nltk corpus gensim word-cloud
Doc2vec: How to get document vectors

How to get document vectors of two text documents using Doc2vec? I am new to this, so it would …

python gensim word2vec
gensim error : no module named gensim

I trying to import gensim. I have the following code import gensim model = gensim.models.Word2Vec.load_word2vec_…

python linux gensim word2vec
gensim word2vec: Find number of words in vocabulary

After training a word2vec model using python gensim, how do you find the number of words in the model's …

python neural-network nlp gensim word2vec
Convert word2vec bin file to text

From the word2vec site I can download GoogleNews-vectors-negative300.bin.gz. The .bin file (about 3.4GB) is a binary format …

python c gensim word2vec
How to use Gensim doc2vec with pre-trained word vectors?

I recently came across the doc2vec addition to Gensim. How can I use pre-trained word vectors (e.g. found …

python nlp gensim word2vec doc2vec
How to get tfidf with pandas dataframe?

I want to calculate tf-idf from the documents below. I'm using python and pandas. import pandas as pd df = pd.…

python pandas scikit-learn tf-idf gensim
How to print the LDA topics models from gensim? Python

Using gensim I was able to extract topics from a set of documents in LSA but how do I access …

python nlp lda topic-modeling gensim
Gensim: KeyError: "word not in vocabulary"

I have a trained Word2vec model using Python's Gensim Library. I have a tokenized list as below. The vocab …

python nlp gensim word2vec topic-modeling