Word Embeddings are a technique in NLP that represent words as continuous vectors in a high-dimensional space. These vectors capture semantic and syntactic relationships between words. Word embeddings are useful for tasks such as language translation, sentiment analysis, and document clustering.
GPT is an advanced language model that uses Deep Learning techniques to generate human-like text. Built on the Transformer architecture, GPT models have been…
