Deep Learning for Nature Language Processing --- 第六講
Overview Today: 一些有用的策略和技巧： 1.多任務學習（multi-task learning） 2.非線性函數（Nonlinearities） 3.檢查求導是否正確（gradient check） 4.Momentum,AdaGrad 語言模型（Language Model） RNN Multi-task learning / Weight sharing 和上一章節提到的NN
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相關文章
- 1. Deep Learning for Nature Language Processing --- 第七講
- 2. Deep Learning for Nature Language Processing --- 第八講
- 3. Deep Learning for Nature Language Processing---第四講(上)
- 4. Deep Learning for Nature Language Processing --- 第五講
- 5. Deep Learning for Nature Language Processing --- 第四講（下）
- 6. CS224d: Deep Learning for Natural Language Process
- 7. 【筆記】CS224N Natural Language Processing with Deep Learning
- 8. 李宏毅：deep learning for language modeling
- 9. Language Understanding for TextGames using Deep Reinforcement
- 10. Recent Trends in Deep Learning Based Natural Language Processing(arXiv)筆記