icmpping

1、自动爬取新闻页面的信息 2、使用Python语言编写(1. Automatic crawling of news page information 2. Writing in Python Language)

Python机器学习——预测分析核心算法(MICHAEL BOWLES teaches machine learning at Hacker Dojo in Silicon Valley, consults on machine learning projects, and is involved in a number of startups in such areas as bioinformatics and high-frequency trading. Following an assistant professorship at MIT, Michael went on to found and run two Silicon Valley startups, both of which went public. His courses at Hacker Dojo are nearly always sold out and receive great feedback from participants.)

说明：  就是用sfm方法把用相机拍摄的图像进行重建三维模型(The SFM method is used to reconstruct the three-dimensional model of the image taken by the camera)

说明：  这个程序用来实现排课，利用的是·遗传算法，但这只是一个简单的程序(to deal with timetable scheduing)

通过python语言实现，利用遗传算法求解二元函数最大值(Using Python language and genetic algorithm to solve the maximum of binary function)

感知器是一种仿生算法，并试图模仿一个单一的神经元，我们简单地乘每个输入（功能）的放大器；重量，并检查是否这个加权求和放大器；（激活）大于一个阈值。放大器；放大器；如果是这样，那么我们“火”的神经元（即决定放大器；根据激活）

python实现实时视频流传输和显示，从客户端到服务器端(Python implements real-time video streaming transmission and display from client to server)

说明：  使用卷积神经网络进行高光谱遥感数据分类，使用的数据源为Pavia University高光谱数据 文件夹log--日志文件夹，存放TensorBorad日志、网络参数文件、混淆矩阵图 文件夹Patch--存放数据处理的切片结果 文件夹PaviaU--高光谱数据下载存放位置 文件夹predicted--CNN对原始影像的分类结果 data.py--对原始高光谱影像进行数据处理，生成切片 net.py--神经网络模型 train.py--训练神经网络 utils.py--需要用到的函数 show.py--使用训练好的神经网络模型对原始数据进行分类(Using convolution neural network to classify hyperspectral remote sensing data, the data source is Pavia University hyperspectral data. Folder log -- Log folder, store TensorBorad logs, network parameter files, obfuscation matrix diagrams Folder Patch -- Stores slice results of data processing Folder PaviaU -- Place for Hyperspectral Data Download and Storage Folder predicted -- CNN classification results of original images Data.py -- Data processing of original hyperspectral images to generate slices Net.py--Neural Network Model Train.py--Training Neural Network Utils. py -- Functions to be used Show.py -- Classification of raw data using trained neural network model)

说明：  MOT领域最经典的算法————SORT，多目标跟踪领域的RCNN(SORT, the most classical algorithm in the field of MOT, is the RCNN in the field of multi-target tracking.)

说明：  Python环境下 愤怒的小鸟 强化学习程序完整版，Qlearning 算法(The full version of Angry Birds Reinforcement Learning Program in Python Environment, Qlearning Algorithm)