很全面的KNN源代码

【实例简介】入门级实例

说明：  对提供的图像进行裁剪，并对裁剪后的图片分类，主要是裁剪边框，提取某个区域的图片(Cut out the details of the pictures and classify the cut pictures.)

经典书籍，think python,第二版。(think python, second edition. written by Allen B. Downey.)

说明：  基于opencv图像处理、人脸识别的疲劳驾驶检测系统(Drowsiness detection based on)

说明：  deep+learning深度学习人工智能资料(deep+learning Deep learning of AI materials)

说明：  python编写，使用sklearn机器学习库里的svm分类器，以MNIST为数据集，手动输入数字分类，MNIST.py为训练代码，训练10000次准确率为93.93%，手动3.py为手动输入并分类的代码。(Written in Python, using the svm classifier in the sklearn machine learning library, using MNIST as the data set, manually input the numeric classification, MNIST.py is the training code, the accuracy of training 10000 times is 93.93%, manual 3.py is manually entered and classified Code.)

说明：  用深度卷积网络实现复制粘贴和图像拼接篡改的检测，定位篡改区域(Using deep learning convolution network CNN to locate image copy-move and image splicing tampering)

利用python爬虫技术爬取豆瓣top250的信息并保存为excel文件

遥感数字图像中影像镶嵌，enviIDL源码下载(Remote sensing digital image image mosaic, envi IDL source code download)

说明：  基于全连接神经网络的基本神经网络分类算法。(A basic neural network classification algorithm based on fully connected neural network)