Design of Recommendation Systems - Recommender Systems Using Deep Learning Explained
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Overview
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Explore the fundamentals of recommender systems and their applications in this comprehensive 59-minute video. Delve into the various types of recommender systems, popular machine learning models, and performance metrics. Learn how to design a baseline recommender system and understand high-level considerations for industry-scale implementations. Gain insights into real-world recommender systems used by major companies. Cover topics including background, motivation, types of recommender systems, recommendation models, and performance metrics design. Enhance your understanding of how these systems are revolutionizing content discovery and improving customer satisfaction across industries like e-commerce, entertainment, and social media.
Syllabus
Background
Introduction and Motivation
Types of Recommender Systems
Recommendation Models
Performance Metrics and its Designs
Taught by
Data Science Dojo
Reviews
4.0 rating, based on 2 Class Central reviews
Showing Class Central Sort
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Best for
Similarity measures
Neighborhood methods
Matrix factorization / SVD
Collaborative filtering
Evaluation metrics (coverage, novelty, serendipity)
Why useful
Your syllabus specifically mentions:
SVD
similarity computation
neighborhood selection
sparsity & cold-start
evaluation metrics -
Good Broad Overview, indepth to be seen but broadly what are recommendation systems for a naive user it is good but in depth or technical or architectural is absent