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Recommender Systems: Foundations, Algorithms, and Recent Advances

Name: Recommender Systems: Foundations, Algorithms, and Recent Advances
Availability: InStock

This course provides a comprehensive introduction to recommender systems, covering basic concepts, recommendation tasks, algorithms, and evaluation methods. It also explores recent topics such as sequential and session-based recommendation, popularity and bias, and the impact and value of recommender systems. Students will gain both theoretical understanding and practical insights into how modern recommendation systems work.

What You'll Learn

Explain the fundamental concepts and tasks of recommender systems

Describe and compare different recommendation algorithms

Evaluate recommender systems using appropriate metrics and methods

Understand recent trends like sequential and session-based recommendation

Analyze issues of popularity, bias, and recurrence in recommendations

Assess the impact and value of recommender systems in real-world applications

About this course

Recommender Systems: Foundations, Algorithms, and Recent Advances is a self-paced beginner-level technology online course on GreyAcademy, taught by Anurag Trivedi. It has 5 modules and 5 chapters, and it takes about 10 hours to complete. The course is free to enrol. You get a completion certificate when you finish all the lessons.

Topics covered: Introduction, Abstract, Basic Concepts, Recent Topics, Bibliography.

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