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Optimizing Recommendations on Wattpad Home
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Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only! Grab it Learn how Wattpad optimizes its homepage recommendation system in this technical conference talk from the Toronto Machine Learning Series. Explore how Senior AI/ML Product Manager Gayathri Srinivasan and Data Scientist Abhimanyu Anand tackle the challenges of balancing multiple business objectives in content recommendations for the world's leading online storytelling platform. Discover the implementation of probabilistic algorithms based on reinforcement learning principles, and understand how the team addresses data sparsity and cold start problems through innovative graph neural network architectures. Gain insights into the evolution of Wattpad's recommendation system as it adapts to new content types and business goals, including user engagement, merchandising, and marketing strategies.

Optimizing Recommendations on Wattpad Home - Building a Multi-Objective Recommender System

Toronto Machine Learning Series (TMLS)
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