[网盘]大数据推荐算法教程
推荐系统企业工程实践项目作为大数据基础应用的延伸，构建于用户画像项目之上。旨在让学员学习搭建企业级推荐系统的基本思路，深入讲解推荐系统中最重要的两个环节，召回和排序，每个环节都介绍了基于Spark-Mllib的相关算法，例如召回层ItemCF，ALS双向召回算法，融合排序层引入GBDT+LR。在理解算法的同时，更注重工程实践。我们将从原始数据中提取特征。深入讲解从算法模型设计到编程实现的转化，同时针对算法模型的跨平台部署方案给出实际案例，让学员了解算法模型的部署和使用在实际项目中。(As an extension of the basic application of big data, the recommendation system enterprise engineering practice project is built on the user portrait project. The purpose is to let students learn the basic idea of ??building an enterprise-level recommendation system, and explain in depth the two most important links in the recommendation system, recall and sorting. Each link introduces related algorithms based on Spark-Mllib, such as the recall layer ItemCF, ALS Two-way recall algorithm, the fusion sorting layer introduces GBDT+LR. While understanding the algorithm, pay more attention to engineering practice. We will extract features from raw data. Explain in depth the transformation from algorithm model design to programming implementation, and give practical cases for the cross-platform deployment of algorithm models, so that students can understand the deployment and use of algorithm models in actual projects.)
页:
[1]