Benjamin Bengfort
Dr. Benjamin Bengfort is the co-founder and CEO of Rotational Labs, where he orchestrates the integration of innovative machine learning techniques with advanced distributed computing systems. A seasoned expert in systems engineering, programming, and data science, he has a proven record of developing AI-driven solutions that support globally distributed data architectures and address the complex challenges of multi-region organizations. Under his leadership, Rotational has focused on not just the implementation but also the responsibility of participating in an AI driven economy; a believer in open source, Dr. Bengfort pays special attention to the ethics and outcomes of AI, ensuring humans are at the center of our solutions. He is the co-author of Applied Text Analysis with Python (2018, O’Reilly) and Data Analytics with Hadoop (2016, O’Reilly). Dr. Bengfort earned his Ph.D. from the University of Maryland focusing on planetary scale distributed systems.
Sessions
Multi-armed bandits are a reinforcement learning tool often used in environments where the cost or rewards of different choices are unknown or where those functions may change over time. The good news is that as far as implementation goes, bandits are surprisingly easy to implement; however, in practice, the difficulty comes from defining a reward function that best targets your specific use case. In this talk, we will discuss how to use bandit algorithms effectively, taking note of practical strategies for experimental design and deployment of bandits in your applications.