Dimensionality reduction methods have been used to represent words with vectors in NLP applications since at least the introduction of latent semantic indexing in the late 1980s, but word embeddings ...

In this video, we will learn about training word embeddings. To train word embeddings, we need to solve a fake problem. This problem is something that we do not care about. What we care about are the ...

One of the main challenges in language analysis is the method of transforming text into numerical input, which makes modeling feasible. It is not a problem in computer vision tasks due to the fact ...