Search
Close this search box.

Cognilytica is now part of PMI!

Glossary of Artificial Intelligence (AI), Machine Learning (ML), and Big Data Terms

Vectorization and Word Embedding

In the context of Natural Language Processing (NLP) systems, word vectorization is the process of mapping words or phrases to a vector across the different dimensions of how a word can be represented based on similarities, semantics, and relationships. The vector, which is a line connecting two points in different dimensions, encodes the meaning of a word such that the words that are closer in the vector space are most probably similar in meaning. Using machine learning approaches, machines can learn how words are related or have similar meaning. Similar words occupy locations close to each other in vector space, whereas words that are dissimilar are far apart. These features can include context, such as when words are used in conjunction or near other words.

Get Certified on the Proven Path to Success with AI, Big Data & Analytics Projects

cropped-CogHeadLogo.png

Register to View Event

cropped-CogHeadLogo.png

Get The Vectorization and Word Embedding

cropped-CogHeadLogo.png

AI Best Practices

Get the Step By Step Checklist for AI Projects

login

Login to register for events. Don’t have an account? Just register for an event and an account will be created for you!