One of the questions that often comes up is what’s the difference between fastText and Word2Vec? Aren’t they both the same? Yes and no. They are conceptually the same, but there is a minor difference—fastText operates at a character level but Word2Vec […]
Word2Vec is a widely used word representation technique that uses neural networks under the hood. The resulting word representation or embeddings can be used to infer semantic similarity between words and phrases, expand queries, surface related concepts and more. The
What are pre-trained embeddings and why? Pre-trained word embeddings are vector representation of words trained on a large dataset. With pre-trained embeddings, you will essentially be using the weights and vocabulary from the end result of the training process done
Training a Word2Vec model with phrases is very similar to training a Word2Vec model with single words. The difference: you would need to add a layer of intelligence in processing your text data to pre-discover phrases. In this tutorial, you
A Hands-On Word2Vec Tutorial Using the Gensim Package The idea behind Word2Vec is pretty simple. We’re making an assumption that the meaning of a word can be inferred by the company it keeps. This is analogous to the saying, “show
