开心麻花影视作品分析(项目源码下载)-Python项目开发案例集锦13.zip

对光学遥感影像进行分类，对特征进行标记，使用SVM、随机森林进行分类预测精度

【实例简介】 PYQT 小说阅读器

零基础学python（明日科技）源代码

16个python基础小例子

gcn

自动化测试示例(基于pytest)

绘制三维直线图，将飞机飞行的航迹用（经度，纬度和高度）来描述

【实例简介】

LSTM入门学习，正弦波序列预测         for i, input_t in enumerate(input.chunk(input.size(1), dim=1)):             h_t, c_t = self.lstm1(input_t, (h_t, c_t))             h_t2, c_t2 = self.lstm2(h_t, (h_t2, c_t2))             output = self.linear(h_t2)  # output.shape:[batch,1]             outputs = [output]  # outputs.shape:[[batch,1],...[batch,1]], list composed of n [batch,1],         for i in range(future):  # if we should predict the future             h_t, c_t = self.lstm1(output, (h_t, c_t))             h_t2, c_t2 = self.lstm2(h_t, (h_t2, c_t2))             output = self.linear(h_t2)  # output.shape:[batch,1]             outputs = [output]  # outputs.shape:[[batch,1],...[batch,1]], list composed of n [batch,1],         outputs = torch.stack(outputs, 1).squeeze(2)  # shape after stack:[batch, n, 1], shape after squeeze: [batch,n]         return outputs

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