| Name | Last modified | Size |
|---|---|---|
| Parent Directory | [DIR] | |
| 10，user_profile缺失值处理-低维数据转高维数据_.mp4 | 2022-February-19 01:57 | 53.32 MiB |
| 11，CTR模型训练-数据准备_.mp4 | 2022-February-19 01:57 | 56.11 MiB |
| 12，CTR模型训练-实现_.mp4 | 2022-February-19 01:57 | 26.32 MiB |
| 13，建立广告类别和广告id的匹配关系_.mp4 | 2022-February-19 01:57 | 73.05 MiB |
| 14，结合redis完成商品召回_.mp4 | 2022-February-19 01:57 | 30.88 MiB |
| 15，完成商品的精选及其总结_.mp4 | 2022-February-19 01:57 | 100.61 MiB |
| 1，作业_.mp4 | 2022-February-19 01:57 | 56.75 MiB |
| 2，项目思路整理和数据集切分_.mp4 | 2022-February-19 01:57 | 38.63 MiB |
| 3，申请spark的资源_.mp4 | 2022-February-19 01:57 | 31.16 MiB |
| 4，spark实现数据的读取和评分数据的构建_.mp4 | 2022-February-19 01:57 | 132.6 MiB |
| 5，保存数据模型及其召回商品到redis_.mp4 | 2022-February-19 01:57 | 32.77 MiB |
| 6，raw_sample数据的读取和处理_.mp4 | 2022-February-19 01:57 | 94.07 MiB |
| 7，ad_feature的数据读取和处理_.mp4 | 2022-February-19 01:57 | 26.47 MiB |
| 8，上午小结_.mp4 | 2022-February-19 01:57 | 11.01 MiB |
| 9，user_profile缺失值处理-利用随机森林对缺失值进行预测_.mp4 | 2022-February-19 01:57 | 128.44 MiB |