| 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 | 55.9 MiB |
| 11，CTR模型训练-数据准备_.mp4 | 2022-February-19 01:57 | 58.83 MiB |
| 12，CTR模型训练-实现_.mp4 | 2022-February-19 01:57 | 27.59 MiB |
| 13，建立广告类别和广告id的匹配关系_.mp4 | 2022-February-19 01:57 | 76.59 MiB |
| 14，结合redis完成商品召回_.mp4 | 2022-February-19 01:57 | 32.37 MiB |
| 15，完成商品的精选及其总结_.mp4 | 2022-February-19 01:57 | 105.49 MiB |
| 1，作业_.mp4 | 2022-February-19 01:57 | 59.5 MiB |
| 2，项目思路整理和数据集切分_.mp4 | 2022-February-19 01:57 | 40.5 MiB |
| 3，申请spark的资源_.mp4 | 2022-February-19 01:57 | 32.67 MiB |
| 4，spark实现数据的读取和评分数据的构建_.mp4 | 2022-February-19 01:57 | 139.04 MiB |
| 5，保存数据模型及其召回商品到redis_.mp4 | 2022-February-19 01:57 | 34.36 MiB |
| 6，raw_sample数据的读取和处理_.mp4 | 2022-February-19 01:57 | 98.63 MiB |
| 7，ad_feature的数据读取和处理_.mp4 | 2022-February-19 01:57 | 27.75 MiB |
| 8，上午小结_.mp4 | 2022-February-19 01:57 | 11.54 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 | 134.67 MiB |