Implementing OddOneOut Algorithm With Word2Vec(in Python)

Implementing OddOneOut Algorithm With Word2Vec(in Python)

Firstly, let's talk about what is a Word2Vec model. Word2Vec is one of the most popular techniques to learn word embeddings using a shallow neural network. It was developed by Tomas Mikolov in 2013 at Google.

Firstly, let’s talk about what is a Word2Vec model. Word2Vec is one of the most popular techniques to learn word embeddings using a shallow neural network. It was developed by Tomas Mikolov in 2013 at Google . For the algorithm Odd One Out that we are going to implement soon, we will use the Google pre-trained model: ‘Googlenews-vectors-negative300.bin’, which can be downloaded from here . This model can be loaded using the gensim module, by the following code:

from gensim.models import KeyedVectors
    model = KeyedVectors.load_word2vec_format('GoogleNews-vectors-negative300.bin',binary=True)
    #model loaded

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