方向：理工
专业：人工智能
适合人群：计算机科学,机器学习,深度学习,人工智能,语言学,人机交互
是否可以加论文：是
项目时长及形式：英文
产出：
7周在线小组科研学习+5周论文辅导学习 共125课时
学术报告
优秀学员获主导师Reference Letter
EI/CPCI/Scopus/ProQuest/Crossref/EBSCO或同等级别索引国际会议全文投递与发表（可用于申请）
结业证书
成绩单
项目介绍：
该项目将全面介绍适用于 NLP 的前沿深度学习网络模型与应用。在模型方面，教授将涵盖单词矢量表示、基于窗口的神经网络、循环神经网络、长期短期记忆模型、卷积神经网络、注意力网络、Transformer，以及近期一些涉及预训练的语言模型的模型。应用方面，我们将研究当前最火热的NLP应用中内部技术，如谷歌翻译，Siri和其他个人助理系统等。在项目中，学生将在导师指导下理解、设计、应用神经网络模型在自然语言处理与人机交互应用中。项目结束时，学生将提交项目报告，进行成果展示。The course provides a thorough introduction to cutting-edge research in deep learning applied to NLP. On the model side, we will cover word vector representations, window-based neural networks, recurrent neural networks, long-short-term-memory models, convolutional neural networks, attention networks, transformers, as well as some recent models involving pre-trained language models. On the application side, we will study the inside techniques of current well-known NLP systems such as Google Translate, Siri, and Personal Assistant Systems. Through lectures and programming assignments students will learn skills to design, implement, and understand the neural network models in practical applications.
个性化研究课题参考 Suggested Research Fields
类Siri智能问答系统 Intelligent Q&A
结合语言特征和Roberta神经模型进行幽默检测 Combine Linguistic Features with Roberta based Neural Model for Humor Detection
各机器翻译平台所用模型及可用性对比 Review of models’ performance of different machine translation platforms
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