Learn Word2Vec

Word2vec is a technique for natural language processing. The word2vec algorithm uses a neural network model to learn word associations from a large corpus of text. Once trained, such a model can detect synonymous words or suggest additional words for a partial sentence. As the name implies, word2vec represents each distinct word with a particular list of numbers called a vector. The vectors are chosen carefully such that a simple mathematical function (the cosine similarity between the vectors) indicates the level of semantic similarity between the words represented by those vectors.

Best Courses in Word2Vec

Stanford CS224N: Natural Language Processing with Deep Learning | Winter 2019


    No SubTopics found

    Quick Links

    Best Courses

    Best ArticlesBest PodcastsBest BooksBest Videos

    © 2021