图 书 馆
深刻的自然语言理解Deep Natural Language Understanding |
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| 课程网址: | http://videolectures.net/deeplearning2016_cho_language_understand... |
| 主讲教师: | Kyunghyun Cho |
| 开课单位: | 纽约大学 |
| 开课时间: | 2016-08-23 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | In this lecture, I start with a claim that natural language understanding can largely be approached as building a better language model and explain three widely-adopted approaches to language modelling. They are n-gram language modelling, feedforward neural language modelling and recurrent language modelling. As I develop from the traditional n-gram language model toward recurrent language model, I discuss the concepts of data sparsity and generalization via continuous space representations. I then continue on to the recent development of a novel paradigm in machine translation based on recurrent language modelling, often called neural machine translation. The lecture concludes with three new opportunities in natural language processing/understanding made possible by the introduction of continuous space representations in deep neural networks. |
| 关 键 词: | 自然语言; 理解; 处理 |
| 课程来源: | 视频讲座网 |
| 数据采集: | 2020-11-27：yxd |
| 最后编审: | 2020-11-27：yxd |
| 阅读次数: | 34 |