NLP之Seq2Seq
https://blog.csdn.net/qq_32241189/article/details/81591456
深度学习的seq2seq模型
https://blog.csdn.net/wangyangzhizhou/article/details/77883152
深度学习笔记(六)：Encoder-Decoder模型和Attention模型
https://blog.csdn.net/u014595019/article/details/52826423?utm_medium=distribute.pc_relevant.none-task-blog-BlogCommendFromMachineLearnPai2-3.compare&depth_1-utm_source=distribute.pc_relevant.none-task-blog-BlogCommendFromMachineLearnPai2-3.compare
三分钟带你对 Softmax 划重点
https://blog.csdn.net/red_stone1/article/details/80687921
RNN & LSTM & GRU 的原理与区别
https://www.cnblogs.com/jins-note/p/9715610.html
Seq2Seq模型 与 Attention 策略
https://www.cnblogs.com/wevolf/p/10886260.html
word2vec的详解
https://www.pianshen.com/article/53911852695/
Word Embedding理解
https://www.cnblogs.com/kjkj/p/9824419.html
https://blog.csdn.net/wzy628810/article/details/106991709
简单认识Adam优化器
https://www.jianshu.com/p/aebcaf8af76e
几种AutoEncoder原理
https://blog.csdn.net/leida_wt/article/details/85052299
VAE全面理解（上）
https://blog.csdn.net/weixin_40955254/article/details/82315224
VAE全面理解（下）
https://blog.csdn.net/weixin_40955254/article/details/82315909
https://blog.csdn.net/weixin_40955254?t=1
GAN网络详解（从零入门）
https://blog.csdn.net/LEE18254290736/article/details/97371930
生成对抗网络（GAN）教程 - 多图详解
https://blog.csdn.net/maqunfi/article/details/82220297?utm_medium=distribute.pc_relevant.none-task-blog-BlogCommendFromMachineLearnPai2-1.compare&depth_1-utm_source=distribute.pc_relevant.none-task-blog-BlogCommendFromMachineLearnPai2-1.compare