Language modeling
應用：語音識別，文字識別 N-gram 怎麼就算出現的機率，P（w1,w2,w3,w4,w5....wn) = P(w1|Start)P(w2|w1).....P(wn|wn-1) 估算P（beach|nice)from training data: P（beach|nice) = C(nice beach)/C(nice)#解釋爲nice beach 出現的次數除以 nice出現的次數 for
相關文章
- 1. Language Modeling
- 2. 【composer開發】Modeling Language
- 3. Language Modeling with N-grams (Speech and Language Processing)
- 4. 【Natural Language Processing】語言模型(Language Modeling)
- 5. LSTM Neural Networks for Language Modeling
- 6. Language Modeling---NLP學習筆記
- 7. Language Modeling with Gated Convolutional Networks
- 8. 學習筆記之UML ( Unified Modeling Language )
- 9. UML(Unified Modeling Language) -- 早期筆記
- 10. Language Modeling with Gated Convolutional Networks ( GLU )理解
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相關文章
- 1. Language Modeling
- 2. 【composer開發】Modeling Language
- 3. Language Modeling with N-grams (Speech and Language Processing)
- 4. 【Natural Language Processing】語言模型(Language Modeling)
- 5. LSTM Neural Networks for Language Modeling
- 6. Language Modeling---NLP學習筆記
- 7. Language Modeling with Gated Convolutional Networks
- 8. 學習筆記之UML ( Unified Modeling Language )
- 9. UML(Unified Modeling Language) -- 早期筆記
- 10. Language Modeling with Gated Convolutional Networks ( GLU )理解