mJackie/RecSys
计算广告/推荐系统/机器学习(Machine Learning)/点击率(CTR)/转化率(CVR)预估/点击率预估
This resource curates learning materials for professionals working on recommendation systems and computational advertising. It provides a comprehensive collection of articles, practical tools, code examples, and classic papers. The output is an enriched understanding and practical approaches to building effective recommendation engines and ad platforms, ideal for data scientists, machine learning engineers, and product managers in e-commerce or ad tech.
2,073 stars. No commits in the last 6 months.
Use this if you are responsible for designing, implementing, or optimizing recommendation systems or online advertising platforms and need to deepen your knowledge or find practical solutions.
Not ideal if you are looking for a plug-and-play software solution or a simple API to integrate into an existing system without needing to understand the underlying models.
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Dec 17, 2019
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