Approximating the Softmax for Learning Word Embeddings
On word embeddings - Part 2: Approximating the Softmax The softmax layer is a core part of many current neural network architectures. When the number of output classes is very large, such as in the case of language modelling, computing the softmax becomes very expensive. This post explores approximations to make the computation more efficient. This post gives an overview of approximations that can
On word embeddings - Part 1
On word embeddings - Part 1 Word embeddings popularized by word2vec are pervasive in current NLP applications. The history of word embeddings, however, goes back a lot further. This post explores the history of word embeddings in the context of language modelling. This post presents the most well-known models for learning word embeddings based on language modelling. Table of contents: A brief hist
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