항목
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Word2vecWord2vec is a group of related models that are used to produce so-called word embeddings. These models are shallow, two-layer neural networks, that are trained to reconstruct linguistic contexts of words: the network is shown a word, and must guess at which words occurred in adjacent positions in...출처 영어 위키백과
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Deeplearning4j Deeplearning4j4j에는 Restricted Boltzmann machine, deep belief net, deep autoencoder, stacked denoising autoencoder, recursive neural tensor network, word2vec, doc2vec, Glove 등의 알고리듬들이 구현 되어 있다. 이 알고리듬은 모두 아파치 하둡과 스파크를 이용해 분산 병렬 처리가 가능하다. Deeplearning4j는 아파치...도서 위키백과
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Deeplearning4jrestricted Boltzmann machine, deep belief net, deep autoencoder, stacked denoising autoencoder and recursive neural tensor network, as well as word2vec, doc2vec and GloVe. These algorithms all include distributed parallel versions that integrate with Hadoop and Spark. It is commercially supported...출처 영어 위키백과
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Gensimcollections, using efficient online algorithms.Gensim includes implementations of tf–idf, random projections, deep learning with Google's word2vec and document2vec algorithms (reimplemented and optimized in Cython), hierarchical Dirichlet processes (HDP), latent semantic analysis (LSA) and...출처 영어 위키백과
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Language modellog-probability \sum_{-k \leq j-1, \, j \leq k} \log P(w_{t+j}w_t) This is called a skip-gram language model, and is the basis of the popular word2vec program.Instead of using neural net language models to produce actual probabilities, it is common to instead use the distributed representation...출처 영어 위키백과
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Semantic similarityall free for research purposes). and , a Java toolkit to compute the similarity between words and phrases. Allows to import word spaces generated with Word2vec. Freely available for research, API is Apache licensed. , a web API to compute semantic relatedness between pairs of words or text...출처 영어 위키백과