LBM-2维扩散

简单数据结构python实现，包括线性表、链表、哈希表、二叉树等(Python implementation of simple data structure, including linear list, linked list, hash table, binary tree, etc.)

说明：  通过直线判断图像的倾斜角度，并将其自动旋转正(Judging the tilt angle of an image by a straight line and automatically rotating it forward)

说明：  基于LSTM的时间序列预测-原理-python代码(Prediction of time series based on LSTM - principles -python code)

machine learning中最经典的图书(The most classic machine books learning)

BP(back propagation)神经网络是1986年由Rumelhart和McClelland为首的科学家提出的概念，是一种按照误差逆向传播算法训练的多层前馈神经网络，是目前应用最广泛的神经网络，py实现(BP (back propagation) neural network is a concept put forward by Rumelhart and McClelland in 1986. It is a multi-layer feedforward neural network trained by error back propagation algorithm. It is the most widely used neural network at present.)

说明：  可以实现EEMD的分解功能，有效的进行风速预测(It can realize the decomposition function of EEMD and effectively predict the wind speed)

说明：  机器学习实战，python源码，KNN,决策树等实现(Machinie Learning IN ACTION)

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

The PLCopen Editor is a software that let you write PLC programs according to IEC-61131-3 and conform to PLCopen XML. It was created mainly by Edouard Tisserant and Laurent Bessard for the Beremiz project. The OpenPLC is capable of running Structured Text (ST) programs. PLCopen Editor can generate ST programs for the OpenPLC out of all the five IEC-61131-3 standard languages:

python学习手册，可供机器学习的同学学习，讲的还是比较好。(Python learning manuals, for machine learning students to learn, speak better.)