What Does Machine Learning Embedding Mean?

Embedding is the process of converting high-dimensional data to low-dimensional data in the form of a vector in such a way that the two are semantically similar. In its literal sense, "embedding" refers to an extract (portion) of anything. Generally, embeddings improve the efficiency and usability of machine learning models and can be utilised with other types of models as well. When dealing with massive amounts of data to train, building machine learning models is a nuisance. As a result, embedding comes into play.