《PyTorch深度学习指南：序列与自然语言处理》札记.docxVIP

《PyTorch深度学习指南：序列与自然语言处理》读书随笔

目录

一、内容概览................................................2

1.1书籍简介.............................................3

1.2作者介绍.............................................4

1.3本书目的.............................................4

二、PyTorch简介.............................................5

2.1PyTorch的发展历程....................................7

2.2PyTorch的特点........................................8

2.3PyTorch的应用场景...................................10

三、深度学习基础...........................................11

3.1机器学习基本概念....................................12

3.2深度学习基本概念....................................13

3.3神经网络的基本结构..................................14

四、PyTorch基础知识........................................15

五、PyTorch进阶知识........................................16

六、序列数据处理...........................................18

6.1文本数据预处理......................................19

6.2周期性序列处理......................................21

6.3非周期性序列处理....................................22

七、自然语言处理...........................................24

7.1NLP基本任务.........................................25

7.2基于Transformer的模型...............................26

7.3BERT模型介绍........................................28

7.4GPT模型介绍.........................................30

八、深度学习模型应用案例...................................31

8.1机器翻译............................................32

8.2文本分类............................................32

8.3情感分析............................................34

8.4问答系统............................................35

九、深度学习模型调优.......................................36

9.1学习率调整策略......................................37

9.2正则化技术..........................................38

9.3批量归一化..........................................39

9.4模型集成............................................40

十、总结与展望.............................................41

10.1本书总结...........................................42

10.2未来发展趋势..............