VladPrytula/ecom-ir-book
Personal notes and code on modern recommendation and search systems. From intuition to PyTorch implementation.
This project helps e-commerce and content platform managers understand and build advanced recommendation systems. It takes raw customer interaction data and product information, and teaches you how to construct models that suggest personalized items. Marketing, product, and data science managers in online retail or media companies who want to improve user engagement and sales would use this.
No commits in the last 6 months.
Use this if you need to design, evaluate, or implement state-of-the-art recommendation engines that adapt quickly to changing customer preferences or market conditions.
Not ideal if you're looking for an off-the-shelf, plug-and-play recommendation system without delving into its underlying theory and code.
Stars
7
Forks
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Language
Jupyter Notebook
License
GPL-3.0
Category
Last pushed
Jul 25, 2025
Commits (30d)
0
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