- Innovation
- Algorithms
- Responsible AI
- Performance Tuning
- Data Ethics
- Quality Assurance
- System Requirements
- Data-Driven Decision-Making
- Applied Machine Learning
- Machine Learning Algorithms
- AI Personalization
- Unsupervised Learning
Basic Recommender Systems
Completed by OTHMANE ANSARI
January 19, 2021
11 hours (approximately)
OTHMANE ANSARI's account is verified. Coursera certifies their successful completion of Basic Recommender Systems
What you will learn
You'll be able to build a basic recommender system.
You'll be able to choose the family of recommender systems that best suits the kind of input data, goals and needs.
You'll learn how to identify the correct evaluation activities to measure the quality of a recommender system, based on goals and needs.
You'll be able to point out benefits and limits of different techniques for recommender systems in different scenarios.
Skills you will gain
