Machine Learning
170 learners
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,
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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