Deep Learning for Nature Language Processing --- 第六讲
Overview Today: 一些有用的策略和技巧： 1.多任务学习（multi-task learning） 2.非线性函数（Nonlinearities） 3.检查求导是否正确（gradient check） 4.Momentum,AdaGrad 语言模型（Language Model） RNN Multi-task learning / Weight sharing 和上一章节提到的NN
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相关文章
- 1. Deep Learning for Nature Language Processing --- 第七讲
- 2. Deep Learning for Nature Language Processing --- 第八讲
- 3. Deep Learning for Nature Language Processing---第四讲(上)
- 4. Deep Learning for Nature Language Processing --- 第五讲
- 5. Deep Learning for Nature Language Processing --- 第四讲（下）
- 6. CS224d: Deep Learning for Natural Language Process
- 7. 【笔记】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)笔记