Corerec
corerec makes it easy to create recommender models.
Listed in categories:
EducationSEOMarketing
Description
CoreRec excels in node recommendations model training and graph visualizations, making it the ultimate tool for data scientists and researchers.
How to use Corerec?
To use CoreRec, import the library and load your data using the provided functions. Build user interactions and utilize the recommendation engines for generating recommendations based on your graph data.
Core features of Corerec:
1️⃣
Intelligent Node recommendation engine
2️⃣
Customizable Transformer model
3️⃣
Support Data Parallelism Processing
4️⃣
PyTorch dataset integration
5️⃣
2D/3D Graph visualization
Why could be used Corerec?
| # | Use case | Status | |
|---|---|---|---|
| # 1 | Personalized recommendations in social networks | ✅ | |
| # 2 | Product recommendations in e-commerce platforms | ✅ | |
| # 3 | Context-aware recommendations based on user interactions | ✅ | |
Who developed Corerec?
CoreRec is created by Vishesh Yadav, who is dedicated to enhancing graph analysis and recommendation systems for developers and researchers.