word2vec | Text | TensorFlow

word2vec is not a singular algorithm, rather, it is a family of model architectures and optimizations that can be used to learn word embeddings from large datasets. Embeddings learned through word2vec have proven to be successful on a variety of downstream natural language processing tasks. These papers proposed two methods for learning representations of words: Continuous bag-of-words model: pred

[ymkjp]

NLPへの適用。手法の説明が大局的で分かりやすい。