Artificial Intelligence
Content-Based Recommendation Systems
Dive into content-based recommendation systems, focusing on feature extraction, similarity measures, and factorization machines. You will learn to utilize item features and user profiles to build personalized models. This course provides hands-on C++ examples, progressing from simple similarity methods to advanced factorization techniques for robust, data-driven recommendations.
C++
5 lessons
22 practices
1 hour
Feature Engineering
Course details
Content Based Recommendation Systems
Merging Track and Author Dataframes by Author ID
Adding a Playtime Feature to the Content Features Table
Building a Unified Content Features DataFrame for Recommendations
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