python之requests爬取亚马逊（国外站）关键词排名

说明：  图像超分辨率技术源码； 基于深度学习的图像超分辨率重建的流程如下[2]： 1.首先找到一组原始图像Image1; 2.将这组图片降低分辨率为一组图像Image2 3.通过各种神经网络结构，将Image2超分辨率重建为Image3(Image3和Image1分辨率一样) 4.通过PSNR等方法比较Image1和Image3，验证超分辨率重建的效果，根据效果调节神经网络中的节点和参数 5.反复执行以上直到第4步的结果比较满意(Image super-resolution technology source code; The process of image super-resolution reconstruction based on deep learning is as follows [2]: 1. First find a set of original images image1; 2. Reduce the resolution of this group of pictures to a group of image2 3. Through various neural network structures, the super-resolution of image2 is reconstructed into image3 (the resolution of image3 is the same as that of image1) 4. Compare image1 and image3 by PSNR and other methods to verify the effect of super-resolution reconstruction, and adjust the nodes and parameters of neural network according to the effect 5. Repeat the above until the result of step 4 is satisfactory)

说明：  图像融合 图像处理（卷积、高斯模糊） 图像融合 图像处理（卷积、高斯模糊）(image hybrid Image fusion image processing (convolution, Gaussian blur) image fusion image processing (convolution, Gaussian blur))

说明：  可以用来训练出模型，并识别出猫或狗，直接可以运行识别猫狗(It can be used to train models and identify cats or dogs. It can run directly to recognize cats and dogs.)

说明：  使用双向LSTM神经网络预测时间序列，70%的训练集(Bidirectional LSTM neural networks are used to predict time series)

多重分形去趋势波动分析法，用于不同时间序列的重分形交叉相关性分析。(Multifractal detrended fluctuation analysis)

说明：  一个普通的小游戏，没有什么功能，就一个游戏(An ordinary little game, no function, just a garbage game.)

python文件，可以对新闻等文本进行分词，然后根据每个词出现的次数进行排序，展示出现次数最多的词语，形成词云。(Python file, can be news and other text segmentation, and then according to the number of times each word to sort, show the most frequently appeared words, the formation of word cloud.)

说明：  利用改进k-means算法对客户进行分类，改进rfm模型(Using improved k-means algorithm to classify customers and improve RFM model)

说明：  1D-CNN的模型、训练与预测。用于时间序列的一种信号处理。(the model of 1D-CNN with trainning and prediction)

关于人员疏散开发的程序,其中包括人员疏散中从众，人与人之间，人与墙之间的摩擦力(it is about evacuation programe, Fire Evacutation Research Project)