auxten/go-ctr

Go DeepLearning based Recommendation Framework

39
/ 100
Emerging

This helps e-commerce and content platforms predict what products or content users are most likely to click on or engage with. It takes historical user interaction data and item information as input, then outputs a personalized score for each item, indicating a user's likelihood of interacting with it. E-commerce managers, content strategists, and anyone running a platform with many items and users would find this useful for improving recommendations.

236 stars. No commits in the last 6 months.

Use this if you need to build a deep learning-powered recommendation system quickly and efficiently for your online platform.

Not ideal if your primary goal is real-time, online learning where the model continuously updates with every new user interaction.

e-commerce content-personalization recommendation-systems user-engagement data-driven-marketing
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 10 / 25
Maturity 16 / 25
Community 13 / 25

How are scores calculated?

Stars

236

Forks

17

Language

Go

License

AGPL-3.0

Last pushed

Dec 14, 2022

Commits (30d)

0

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