Applied Reinforcement Learning for Online Ads and Recommender Systems

Explore the transformative power of Reinforcement Learning in online advertising through this 43-minute conference talk. Delve into the $480 billion revenue stream projected for online ads by 2025, and discover how Machine Learning is revolutionizing the industry with real-time, personalized content delivery. Examine the business aspects of fine-tuned customer segments, A/B test optimization, and uplift modeling. Uncover the technical intricacies of stochastic and contextual bandit algorithms, and learn how Reinforcement Learning integrates into real-world Ads/Recommender systems. Gain insights into end-to-end data pipelines and essential metrics, covering latency, scalability, and more. Perfect for those interested in the intersection of AI, marketing, and data science in the rapidly evolving digital advertising landscape.

- Intro
- Overview of Online Ads/Recommender: Business context/Tech impact
- Role of Data Science, ML, and Main ML Tech Challenges
- Overview of Reinforcement Learning for Ads
- Takeaways