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This analytic is a train deep learning network that can play the game Connect 4. It uses the TensorFlow Python library and a dense neural network. The network has 84 inputs node representing the board squares, 168 intermediate nodes, and 7 output nodes representing the best place to move. This network was trained by having the network play itself and playing other strategies.
别名: @connect4
类别: Data
Tags: games, data, deep learning, tensorflow
创建: Apr 14 2021, by: admin
大拇指: 1, 拇指下: 0, 星星: 5.0
连接: 30, 今天: 0, 周: 0, 一个月: 7
最后连接: Dec 5, 15:56

This analytic is a train deep learning network that can play checkers. It uses the TensorFlow Python library and a dense neural network. The network has 128 inputs node representing the checkers board squares, 256 intermediate nodes, and 32 output nodes representing the best piece to move. This network was training by having the network play itself and playing other strategies.
别名: @checkers(tensorflow)
类别: Data
Tags: tensorflow, deep learning, checkers, data, games
创建: Aug 24 2020, by: admin
大拇指: 0, 拇指下: 0, 星星: 0.0
连接: 16, 今天: 0, 周: 0, 一个月: 0
最后连接: Nov 30 2021, 8:16

This analytic is a train deep learning network that can play checkers. It uses the Bot Libre neural network Java library and a dense neural network. The network has 128 inputs node representing the checkers board squares, 256 intermediate nodes, and 32 output nodes representing the best piece to move. This network was training by having the network play itself and playing other strategies.
别名: @checkers(botlibre)
类别: Data
Tags: deep learning, data, checkers, games, botlibre
创建: Aug 24 2020, by: admin
大拇指: 0, 拇指下: 0, 星星: 0.0
连接: 7, 今天: 0, 周: 0, 一个月: 0
最后连接: Oct 11, 12:22

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