Welcome to Recommendation Systems! We've designed this course
to expand your knowledge of recommendation systems and explain
different models used in recommendation, including matrix
factorization and deep neural networks.
[null,null,["Last updated 2024-07-26 UTC."],[[["This course provides a comprehensive overview of recommendation systems and their various models, including matrix factorization and deep neural networks."],["Learners will gain an understanding of the key components of recommendation systems, such as candidate generation, scoring, and re-ranking, as well as the use of embeddings."],["The course requires prior knowledge of machine learning concepts and familiarity with linear algebra."],["Upon completion, learners should be able to describe the purpose of recommendation systems and develop a deeper understanding of common techniques used in candidate generation."],["The estimated time commitment for this course is approximately 4 hours."]]],[]]