Machine Learning
Content-Based Recommendation Systems
In this course, learners will dive into content-based recommendation systems, focusing on factorization machines and Deep Structured Semantic Models (DSSM). These approaches utilize item features and user profiles to make recommendations. The course provides hands-on coding examples to demonstrate how to develop content-based models that harness rich data for personalized recommendations.
Python
5 lessons
22 practices
4 hours
Badge for Machine Learning Model Development,
Machine Learning Model Development
Course details
Content Features Extraction in Recommendation Systems
Link Videos with Channels Using Dataframes
Enhance Features with Playtime
Unifying Game Data for Recommendations
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