之前已经:
【NLP培训教程学习笔记:第1节 » 课时1 NLP发展历史介绍和展望】
现在继续。
![](https://www.crifan.com/files/pic/uploads/2021/03/4430a07a9abf432eb9493d5a6c6ace7b.jpg)
- 概率和信息论
- 分类和回归模型
- 监督学习、半监督学习和非监督学习
![](https://www.crifan.com/files/pic/uploads/2021/03/2fde0ae4da2c42bd8b17ffcce5c2e652.jpg)
statistical inference
![](https://www.crifan.com/files/pic/uploads/2021/03/ce0b30e9716f454abce9263e720e7326.jpg)
![](https://www.crifan.com/files/pic/uploads/2021/03/1d13e703f7194c028d5cc65bcc35a640.jpg)
P:Ω -> [0, 1]
P(A)
![](https://www.crifan.com/files/pic/uploads/2021/03/2e07485779fa4c1daf1c3079ca70ebd4.jpg)
![](https://www.crifan.com/files/pic/uploads/2021/03/2e9e4f54feb54e088169fbb8088f1fc2.jpg)
Joint probability 联合概率
![](https://www.crifan.com/files/pic/uploads/2021/03/22cd878064b649ff8a0a75cc63bcb928.jpg)
Chain Rule 链式法则
![](https://www.crifan.com/files/pic/uploads/2021/03/1ea06844b96046b8ba67d31dc19c98e8.jpg)
A和B无关的时候
![](https://www.crifan.com/files/pic/uploads/2021/03/c4b4c71b8a804ec887311f1f59a0d629.jpg)
Bayers’ Theorem 贝叶斯理论
![](https://www.crifan.com/files/pic/uploads/2021/03/f3bd2b717a1844b3a7ee8a0a7ae4d612.jpg)
Random Variables 随机变量
![](https://www.crifan.com/files/pic/uploads/2021/03/bd682c49bc624aa3bc682e7b7b79c870.jpg)
期望 Expectation
![](https://www.crifan.com/files/pic/uploads/2021/03/b41550c3cd324d4b9ca69f3838cc15a7.jpg)
Variance 方差
![](https://www.crifan.com/files/pic/uploads/2021/03/e461e079701448f8911b477418c6c116.jpg)
语言模型Language Model
![](https://www.crifan.com/files/pic/uploads/2021/03/64f048ccf0eb49aa989a4a023de8c7f1.jpg)
P 概率
- 频率学派 Frequentist statistics
- 贝叶斯学派 Bayesian statistics