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理论和代码-深度学习技巧 | 余道技术

https://yudao.me/2020/04/22/%E7%90%86%E8%AE%BA%E5%92%8C%E4%BB%A3%E7%A0%81-%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E6%8A%80%E5%B7%A7/#more

实际操作过程中,常见的深度学习场景,基本上会在数据筛选、数据处理、模型结构调整、训练参数调整等,常见的可操作的点有:1,数据预处理相关,数据集合选取,数据集预处理,训练集与测试集比例和划分2,模型和调参数相关,模型设计和调整,learning rate, epoch, batch_size,激活函数,dropout,归一化,损失函数选择,优化算法选择/梯度下降类型选择

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