Machine Learning, NLP, Naturallanguageprocessing, Data Science, Word Embeddings.
its unique dimension. In addition, they are mapped into a vector space. Why? The idea behind it is that words with similar context occupy close spatial positions. In other words, words used in a similar context are close to each other while words that aren’t are far away from each other in the