图 书 馆
使用Photon ML构建推荐系统Building Recommender Systems using Photon ML |
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| 课程网址: | http://videolectures.net/kdd2016_tutorial_recommender_systems/ |
| 主讲教师: | Bee-Chung Chen; Bee-Chung Chen; Josh Fleming; Xianxing Zhang; Paul Ogilvie; Deepak Agarwal |
| 开课单位: | LinkedIn公司 |
| 开课时间: | 2016-09-16 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | Recommendation systems have become ubiquitous for web applications. Given significant heterogeneity in user preference, providing personalized recommendations is key to the success of such systems. To achieve this goal at scale, using machine learned models to estimate user preference from user feedback data is essential. Providing an easy-to-use and flexible machine learning library for practitioners to build personalization models is the key to productivity, agility, and developer happiness. In this tutorial, we first give an overview of the components required for building an end-to-end web recommender system and then focus on how to use Photon ML (LinkedIn’s open-sourced machine learning library) to train recommendation models and serve the results to users. Participants will get hands-on experience in training models of different levels of granularity to improve model performance and perform the “modeling loop” consisting of training a model, scoring candidate items using the model, seeing recommended items in a web UI, giving feedback to a number of recommended items, and then training a model again using the newly generated feedback. |
| 关 键 词: | 缩放优化; 图形模型推理; 设计模式 |
| 课程来源: | 视频讲座网 |
| 数据采集: | 2022-11-18：chenjy |
| 最后编审: | 2022-11-18：chenjy |
| 阅读次数: | 32 |