RECOMMENDATION TOOLS
Année du cours : 1 année(s)
Etablissement : IÉSEG School of Management
Langue : English
Formation(s) dans laquelle/lesquelles le cours apparait :
Période : S2
Students should have a basic knowledge of the R programming language.
Basic knowledge of matrix algebra.
At the end of the course, the student should be able to:
– understand the basics of recommendation tools
– distinguish different recommendation algorithms including their advantages and disadvantages
– create simple recommendation algorithms
– evaluate and compare recommendation tools
– build a REST API to communicate with recommendation systems
– know current hot topics in recommendation tools
These competencies and/or skills contribute to the following learning objectives
– 2.B Solve professional dilemmas using concepts of CSR and ethics
– 3.C Organize change management processes
– 5.C Employ state-of-the-art management techniques
– 7.C Effectively apply in-depth specialized knowledge to take advantage of contemporary opportunities in their professional field
• Introduction to recommendation tools.
• Non-personalized recommendation tools.
• Collaborative filtering (theory and hands-on programming).
• Content-based recommendation tools (theory and hands-on programming).
• Hybrid recommendation tools (theory and hands-on programming).
• Evaluating recommendation tools (theory and hands-on programming).
• Current topics in recommendation tools research.
