17.3开运算

基于BOW的图像分类，包含了训练集和测试集合，在控制台下运行

python语言实现k-means算法和Fast Search And Find Of Density Peaks算法用于文本聚类，(python language implements k-means algorithm and Fast Search And Find Of Density Peaks for text clustering algorithm,)

在很多动作大片中，开启关键之门的密码都是人脸———通过摄像头扫描脸部特征，符合则自动开启大门，反之警铃大作。依次通过人脸检测、人脸对齐、人脸识别三个模块，才能完成验证。人脸支付存在的一大问题就是识别率不高，完美光线下识别率能达到90%，特殊光影下只有60%。以淘宝为例，每天上亿的交易量，即便是99.99%也是远远不够的。

说明：  这是使用Python实现的DBScan。像Numpy、熊猫这样的图书馆也被使用过。DBScan算法已经在两个变色龙数据集t4.8k和t5.8k上进行了测试。然后利用matplotlib将得到的结果可视化。为了便于比较，本文将所得到的输出结果与DBScan实现的skLearning库的结果进行了比较。计算每个数据集的同质性和分离度，以观察簇间的相似性和不同的度量。epsilon和min值分别为8.5和16.5。(This is a DBScan implemented using Python. Libraries like Numpy and Panda have also been used. DBScan algorithm has been tested on two chameleon datasets t4.8k and t5.8k. Then the results are visualized by matplotlib. In order to facilitate comparison, the output results are compared with those of skLearning library implemented by DBScan. The homogeneity and segregation of each data set are calculated to observe the similarity and different measures between clusters. Epsilon and min were 8.5 and 16.5 respectively.)

【实例简介】超级玛丽小游戏

说明：  using python ro create a morse audio and demod it

在平时做作业留下来的代码，希望可以帮到那些需要的朋友们。

说明：  《深度学习与图像识别：原理与实践》 及内容实现python代码("Deep learning and image recognition: principle and practice" and content implementation of Python code)

这个通过例子学python的资料，是从一个python学习的网站上下下来的，通过一个个编程实例来学习python，我认为这是学习python一个非常高效的途径。(Learn python this information by example, learning from a web site up and down down the python, and through a months programming examples to learn python, I think this is a very efficient learning python way.)

说明：  关于梅尔谱图提取的一段小程序，用python写(A small program about the extraction of Mel spectrum, written in python)