caszhang / data Goto Github PK
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步骤1:模型假设,如何选择模型;这里选概率模型,以二分类为例,$p(c_{1}|x)=\frac{p(x|c_{1}).p(c_{1})}{p(x|c_{1}).p(c_{1}) + p(x|c_{2}).p(c_{2})},$$如果p(c_{1}|x) > 0.5, x\in c_{1} 否则x \in c_{2}$
学习和理解区块链一个比较好的方法是自己动手写一个,代码的运行环境是python3.6,web框架用的是Flask,环境配置代码如下:
https://yudao.me/2020/03/30/%E6%AF%8F%E6%97%A5%E4%B8%80%E7%82%B9-%E5%85%B3%E4%BA%8EIP/
IP地址就是给网上的每一个主机/路由器/设备(确切说是每一块网卡)分配一个唯一的标识符,ipv4是一个32位的整数,ipv6是128位。
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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