Данные
Аналитика для обработки данных.
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.
Псевдоним: @checkers(botlibre)
Категории: Data
Tags: games, botlibre, checkers, deep learning, data
Создан: Nov 11 2020, by: admin
Недурно: 0, большие пальцы вниз: 0, звезды: 0.0
Соединяет: 1, сегодня: 0, неделю: 0, месяц: 0
Последние Подключения: Nov 11 2020, 13:37
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.
Псевдоним: @checkers(tensorflow)
Категории: Data
Tags: tensorflow, data, deep learning, checkers, games
Создан: Nov 11 2020, by: admin
Недурно: 0, большие пальцы вниз: 0, звезды: 0.0
Соединяет: 1, сегодня: 0, неделю: 0, месяц: 0
Последние Подключения: Nov 11 2020, 13:40
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.
Псевдоним: @connect4
Категории: Data
Tags: deep learning, tensorflow, games, data
Создан: Apr 14 2021, by: admin
Недурно: 0, большие пальцы вниз: 0, звезды: 0.0
Соединяет: 1, сегодня: 0, неделю: 0, месяц: 0
Последние Подключения: Apr 14 2021, 14:44
