Word2Vec, short for “word to vector,’ is a technology used to represent the relationships between different words in the form of a graph. This technology is widely used in machine learning for embedding and text analysis. In this article, we will explore the notion and mechanics of generating embeddings.
Table of contents
What is a word embedding?What’s the difference between word representation, word vectors, and word embeddings?What is Word2Vec?How is Word2Vec trained?Where to find the training data?Why is Word2Vec revolutionary?What are the limitations of Word2Vec?What are the applications of W2V?ConclusionSort: