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Machine learningDeep learning / NLP / CV

Gated Recurrent Unit (GRU)

Gated Recurrent Unit (GRU), iliyoanzishwa na Cho et al. mwaka 2014, ni mtandao wa neva unaojirudia uliorahisishwa ambao hutumia milango miwili iliyojifunza — lango la kusasisha na lango la kuweka upya — ili kuhifadhi au kutupa taarifa kwa kuchagua kwa muda, ikiwezesha uundaji wa mfuatano wenye ufanisi na vigezo vichache kuliko LSTM.

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Vyanzo

  1. Cho, K., van Merrienboer, B., Gulcehre, C., Bahdanau, D., Bougares, F., Schwenk, H., & Bengio, Y. (2014). Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation. In Proceedings of EMNLP 2014, pp. 1724–1734. link
  2. Chung, J., Gulcehre, C., Cho, K., & Bengio, Y. (2014). Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling. NIPS 2014 Deep Learning Workshop. link

Jinsi ya kunukuu ukurasa huu

ScholarGate. (2026, June 3). Gated Recurrent Unit (GRU). ScholarGate. https://scholargate.app/sw/deep-learning/gated-recurrent-unit

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ScholarGateGated Recurrent Unit (Gated Recurrent Unit (GRU)). Imepatikana 2026-06-15 kutoka https://scholargate.app/sw/deep-learning/gated-recurrent-unit · Seti ya data: https://doi.org/10.5281/zenodo.20539026