| 文件 | 时间 | 大小 | 操作 | |
|---|---|---|---|---|
|
说明 2022-09-03 10:09:14 | |||
|
7-1 序列式问题.mp4 | 2022-09-03 10:09:14 | 15.56 MB | |
|
|
7-10 超参数定义.mp4 | 2022-09-03 10:09:14 | 54.51 MB | |
|
|
7-11 词表封装与类别封装.mp4 | 2022-09-03 10:09:14 | 123.21 MB | |
|
|
7-12 数据集封装.mp4 | 2022-09-03 10:09:14 | 128.61 MB | |
|
|
7-13 计算图输入定义.mp4 | 2022-09-03 10:09:14 | 87.69 MB | |
|
|
7-14 计算图实现.mp4 | 2022-09-03 10:09:14 | 73.73 MB | |
|
|
7-15 指标计算与梯度算子实现.mp4 | 2022-09-03 10:09:14 | 64.45 MB | |
|
|
7-16 训练流程实现.mp4 | 2022-09-03 10:09:14 | 122.27 MB | |
|
|
7-17 LSTM单元内部结构实现.mp4 | 2022-09-03 10:09:14 | 216.4 MB | |
|
|
7-18 TextCNN实现.mp4 | 2022-09-03 10:09:14 | 127.03 MB | |
|
|
7-19 循环神经网络总结.mp4 | 2022-09-03 10:09:14 | 3.31 MB | |
|
|
7-2 循环神经网络.mp4 | 2022-09-03 10:09:14 | 77.68 MB | |
|
|
7-3 长短期记忆网络.mp4 | 2022-09-03 10:09:14 | 26.33 MB | |
|
|
7-4 基于LSTM的文本分类模型(TextRNN与HAN).mp4 | 2022-09-03 10:09:14 | 35.97 MB | |
|
|
7-5 基于CNN的文本分类模型(TextCNN).mp4 | 2022-09-03 10:09:14 | 50.71 MB | |
|
|
7-6 RNN与CNN融合解决文本分类.mp4 | 2022-09-03 10:09:14 | 44.37 MB | |
|
|
7-7 数据预处理之分词.mp4 | 2022-09-03 10:09:14 | 123.95 MB | |
|
|
7-8 数据预处理之词表生成与类别表生成.mp4 | 2022-09-03 10:09:14 | 72.16 MB | |
|
|
7-9 实战代码模块解析.mp4 | 2022-09-03 10:09:14 | 19.3 MB | |