Real-Time Machine Learning with Node.js by Philipp Burckhardt, Carnegie Mellon University

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Real-Time Machine Learning with Node.js – Philipp Burckhardt, Carnegie Mellon University Real-time machine learning provides statistical methods to obtain actionable, immediate insights in settings where data becomes available in sequential order. After providing an overview of state of the art real-time machine learning algorithms, we discuss how these algorithms can […]

Machine Learning Tetris

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This algorithm uses a reinforcement learning technique to learn how to play Tetris. It developed a policy on how to select the best action based upon four features of the board: aggregate height, unevenness, maximum height, and number of holes. It performed stochastic gradient ascent to achieve the highest score, […]