i-Jayus/RecSystem-Pytorch
推荐系统论文算法实现，包括序列推荐，多任务学习，元学习等。 Recommendation system papers implementations, including sequence recommendation, multi-task learning, meta-learning, etc.
This project provides modern recommendation system algorithms to help e-commerce platforms, content providers, and digital advertisers better suggest products or content to users. It takes user behavior data (like clicks, purchases, and browsing history) and outputs highly relevant recommendations, improving user engagement and conversion rates. Data scientists and machine learning engineers working on improving user recommendations would use this.
255 stars. No commits in the last 6 months.
Use this if you need to implement or evaluate advanced recommendation algorithms, especially those focusing on multi-task learning for conversion rate prediction or modeling user's sequential behavior.
Not ideal if you are looking for a plug-and-play recommendation system solution without needing to dive into the underlying model architectures or if you require algorithms specifically for collaborative filtering or matrix factorization.
Stars
255
Forks
33
Language
Python
License
MIT
Category
Last pushed
May 26, 2023
Commits (30d)
0
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