Remember our whitepaper “Guide to Recommendation Systems. Implementation of Machine Learning in Business” from the middle of last year? Our data scientist, Michal Stawikowski, did an excellent job of giving you a cross-sectional overview of the issues related to recommender systems. In his paper, we analyzed the issue from both the business side and dived into the technical details. We also presented an example of a four-step recommender system, where in successive steps the results are retrieved, filtered, scanned and sorted. You can also find out what QuickStart ML Blueprints are and how they can help data scientists and engineers with building recommendation systems. Download the white paper here.
Personalised news recommendation systems
Written by
Adam Cierlik
Our Ideas
Explore More Blogs
AI Revolution in Data Extraction: Structuring Emails, PDFs, and Videos
Let us explore some of the real-world use cases, emerging from this conversation, showing how generative AI is redefining what's possible.
Klaudia Wachnio
Contact