How Netflix Knows What You’ll Watch Next | Data Science & Recommendation Systems Explained скачать в хорошем качестве

How Netflix Knows What You’ll Watch Next | Data Science & Recommendation Systems Explained

Ever wondered how streaming platforms pick the perfect show for you? In this exclusive IIT Guwahati webinar, Prof. Sanasam Ranbir Singh breaks down the fascinating world of recommendation systems — the technology behind Netflix, Amazon Prime, YouTube, and even Google Search. 📌 What this video covers (simple, exact explanations): -The two basic approaches used in recommender systems: content-based filtering (use item attributes) and collaborative filtering (use feedback from similar users). How user-item data is represented (the ratings/interaction matrix), why it’s often sparse, and how systems predict missing entries. Representation learning — turning items and users into feature vectors that models can use. A brief look at graph views/graph algorithms for connections between users and items. The role of context and external factors (e.g., media/popularity) in recommendations. A short, contextual mention of deep learning / neural networks as advanced/related approaches. 🎯 Who should watch: students and beginners who want a clear, non-technical entry into how recommendation systems work. (This session starts with fundamentals suitable for first-year learners.) Explore the full programme details and begin your application here: 🔗 https://www.coursera.org/degrees/bach... #NetflixRecommendations #DataScience #MachineLearning #RecommendationSystems #IITGuwahati #AI #TechExplained #StreamingAlgorithms #CollaborativeFiltering #MovieRecommendations