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Basic Recommender Systems に戻る

EIT Digital による Basic Recommender Systems の受講者のレビューおよびフィードバック



This course introduces you to the leading approaches in recommender systems. The techniques described touch both collaborative and content-based approaches and include the most important algorithms used to provide recommendations. You'll learn how they work, how to use and how to evaluate them, pointing out benefits and limits of different recommender system alternatives. After completing this course, you'll be able to describe the requirements and objectives of recommender systems based on different application domains. You'll know how to distinguish recommender systems according to their input data, their internal working mechanisms, and their goals. You’ll have the tools to measure the quality of a recommender system and to incrementally improve it with the design of new algorithms. You'll learn as well how to design recommender systems tailored for new application domains, also considering surrounding social and ethical issues such as identity, privacy, and manipulation. Providing affordable, personalised and high-quality recommendations is always a challenge! This course also leverages two important EIT Overarching Learning Outcomes (OLOs), related to creativity and innovation skills. In trying to design a new recommender system you need to think beyond boundaries and try to figure out how you can improve the quality of the predictions. You should also be able to use knowledge, ideas and technology to create new or significantly improved recommendation tools to support choice-making processes and strategies in different and innovative scenarios, for a better quality of life....



Basic Recommender Systems: 1 - 5 / 5 レビュー

by Adrien B


This course is really not worth the money. You can take it as a very shallow introduction to recommender systems but don't pay for it. There are a lot of free available materials online. The content is really poor. Apart from the introductory (videos) that are of poor quality by the way, the others lessons are not even given by a real person. They are just slides red by a machine. But the worst part is that apart from the quizzes there is 0 home assignments. The only assignments are things like: Take some time to think about this and write your thoughts in this textbox => USELESS

by Jbene M


I learned a lot from this quick course about Recommender systems.

by Ruslan T


There is a nice introduction to recommender systems field

by Amber A


Wish there were notebook examples and/or more hands on.

by Ravikumar R N


Well tailored content