Recommender Systems Capstone
About this Course
This capstone project course for the Recommender Systems Specialization brings together everything you\'ve learned about recommender systems algorithms and evaluation into a comprehensive recommender analysis and design project. You will be given a case study to complete where you have to select and justify the design of a recommender system through analysis of recommender goals and algorithm performance. Learners in the honors track will focus on experimental evaluation of the algorithms against medium sized datasets. The standard track will include a mix of provided results and spreadsheet exploration. Both groups will produce a capstone report documenting the analysis, the selected solution, and the justification for that solution.Created by: University of Minnesota
Related Online Courses
Understanding how pathogens cause infections and how infectious diseases are transmitted is crucial for preventing and controlling the spread of illnesses. In this course, you will learn how... more
This course will provide an in-depth exploration of desktop 3D printing hardware. It will examine the history of desktop 3D printing and demonstrate how 3D printers are made and how they work. This... more
Course Description\\n\\nThis specialization is intended for both students and businesses who aim to learn more about how Cloud technology can help them grow. With Cloud Computing, Big Data, and... more
In this course, you will learn how to work with the Azure command line and web portal to create, manage, and control cloud-based resources. You will look at all three approaches to deploying cloud... more
Discover the basic concepts of cluster analysis, and then study a set of typical clustering methodologies, algorithms, and applications. This includes partitioning methods such as k-means,... more
Powered by
