This course, which is designed to serve as the first course in the Recommender Systems specialization, introduces the concept of recommender systems, reviews several examples in detail, and leads you through non-personalized recommendation using summary statistics and product associations, basic stereotype-based or demographic recommendations, and content-based filtering recommendations.
Об этом курсе
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Лучшие отзывы о курсе INTRODUCTION TO RECOMMENDER SYSTEMS: NON-PERSONALIZED AND CONTENT-BASED
An excellent in-depth introduction into the concepts around recommendation systems!
Overall, the class is perfect. But if you could supply a sample of honour class when we have finished honour codes, it would be perfect.
Great, thorough introduction with tracks for both Java programmers and non-programmers.
As a software engineer with computer science background I found that course enhancing my knowledge. I'm going to continue the specialization.
Специализация Рекомендательные системы: общие сведения
A Recommender System is a process that seeks to predict user preferences. This Specialization covers all the fundamental techniques in recommender systems, from non-personalized and project-association recommenders through content-based and collaborative filtering techniques, as well as advanced topics like matrix factorization, hybrid machine learning methods for recommender systems, and dimension reduction techniques for the user-product preference space.
Часто задаваемые вопросы
Когда я получу доступ к лекциям и заданиям?
Что я получу, оформив подписку на специализацию?
Можно ли получить финансовую помощь?
How does this course relate to the prior versions of "Introduction to Recommender Systems"?
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