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    Semi-uniform strategies for solving K-armed bandits

    In a previous blog post we introduced the K-armed bandit problem - a simple example of allocation of a limited set of resources over time and under uncertainty. We saw how a...

    Reinforcement Learning: The K-armed bandit problem

    In a previous blog post we talked about the foundations of reinforcement learning. We covered classical and operant conditioning, rewards, states,...

    What Is Reinforcement Learning and How Is It Used?

    When you do something well, you’re rewarded. This simple principle has guided humans since the beginning of time, and now, more than ever before, it...

    Evaluating Ray: Distributed Python for Massive Scalability

    Dean Wampler provides a distilled overview of Ray, an open source system for scaling Python systems from single machines to large clusters. If you...

    Deep Reinforcement Learning

    This article provides an excerpt "Deep Reinforcement Learning" from the book, Deep Learning Illustrated by Krohn, Beyleveld, and Bassens. The article...

    Themes and Conferences per Pacoid, Episode 2

    Paco Nathan's column covers themes of data science for accountability, reinforcement learning challenges assumptions, as well as surprises within AI...

    AI in the Enterprise: Making Corporations Smart Again

    In this Data Science Popup session, Danny Lange, VP of AI and Machine Learning at Unity Technologies, gives an inside look at practical applications...

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