Practical Reinforcement Learning

开始时间: 02/22/2020 持续时间: Unknown

所在平台: Coursera

课程类别: 其他类别

大学或机构: CourseraNew

   

课程主页: https://www.coursera.org/learn/practical-rl

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Welcome to the Reinforcement Learning course. Here you will find out about: - foundations of RL methods: value/policy iteration, q-learning, policy gradient, etc. --- with math & batteries included - using deep neural networks for RL tasks --- also known as "the hype train" - state of the art RL algorithms --- and how to apply duct tape to them for practical problems. - and, of course, teaching your neural network to play games --- because that's what everyone thinks RL is about. We'll also use it for seq2seq and contextual bandits. Jump in. It's gonna be fun! Do you have technical problems? Write to us: coursera@hse.ru

实用强化学习:欢迎参加强化学习课程。 在这里您将发现: -RL方法的基础:价值/政策迭代,q学习,政策梯度等。 ---数学与包含电池 -将深度神经网络用于RL任务 ---也被称为“炒作火车” -最新的RL算法 ---以及如何将胶带粘在上面以解决实际问题。 -当然,还可以教您的神经网络玩游戏 ---因为这就是每个人都认为RL的意义。我们还将它用于seq2seq和上下文强盗。 跳进去。会很有趣的! 你有技术上的问题吗?写信给我们:coursera@hse.ru

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The goal of «Intro to Reinforcement learning» is in its name: introduce students to reinforcement le

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