Unravelling Recommender Systems
July 12, 2020
Cofounder & Chief Data Scientist at Tatras Data
E-commerce and retail companies are leveraging the power of data and boosting sales by implementing #recommender systems on their websites. The use cases of these systems have been steadily increasing within the last years and it’s a great time to dive deeper into this amazing machine learning technique. In this webinar, 3AI Thought Leader, Sarabjot Singh, will provide a practical overview of recommender systems. First, three major systems are reviewed: content-based, collaborative filtering, and hybrid, followed by discussions on cold start, scalability, interpretability, and exploitation/exploration. Key Takeaways 1. Describe the purpose of recommendation systems. 2. Understand the components of a recommendation system including candidate generation, scoring, and re-ranking. 3. Develop a deeper technical understanding of common techniques used in candidate generation.