人脸检测

说明：  机器学习的相关内容，通过数据训练，实现线性回归预测问题。(Through data training, the problem of linear regression prediction is realized.)

使用“部分匹配”的方法，你可以通过制造商零件编号搜索零件（MPN）或经销商编号（SKU），甚至限制你的结果到一个特定的制造商或经销商。

说明：  针对地理学、地理信息系统、遥感技术与应用等专业的技术人员，在使用ArcGIS软件绘图时，可以采用Python 中Arcpy 模块，实现批量处理。 针对栅格数据即遥感影像，在对图像进行分析时，如变化检测，土地覆盖类型提取等。这些都需要依据光谱特征对图像进行分类，并对分类后的结果进行标记。(For the technical personnel of geography, GIS, remote sensing technology and application, arcpy module in Python can be used to realize batch processing when drawing with ArcGIS software. For raster data, that is, remote sensing image, in the analysis of the image, such as change detection, land cover type extraction and so on. All of these need to classify the image according to the spectral characteristics and label the classified results.)

用PYQT进行GUI的详细资料，可以对照参考。。。。。。(The detailed information of GUI with PYQT can be compared to reference. The detailed information of GUI with PYQT can be compared to reference.)

说明：  将一张【工作薄】中多张【工作表】汇总成一张表。(Combine a worksheet and multiple sheets into one table.)

这段代码描述多目标遗传算法NSGAII算法的实现，抓要包含三部分：Non-dominated sort， Crowding distance assignment， the selection process来找到pareto-front(The basic operations being performed and the worst case complexities associated with are as follows: Multi-objective evolutionary algorithms which uses non-dominated sorting to find pareto front. It is consist of tree parts: • Non-dominated sort returns a list of the non-dominated fronts F. (O(mN 2 )) • Crowding distance assignment is O(mNlogN) • The crowed comparison operator (Sort on ≥ n) guides the selection process at the various stages of the algorithm towards a uniformly spread out Pareto-optimal front. (O(2Nlog(2N))))

一种关于图像阈值分割的算法，自己试过很好用。(An image threshold segmentation algorithm, I have tried it very well.)

旨在系统介绍人工智能的基本原理、方法和技术，并反映国内外研究和应用的最新进展(The purpose of this paper is to systematically introduce the basic principles, methods and techniques of AI, and to reflect the latest research and application progress at home and abroad.)

说明：  斯坦福大学自动驾驶城市挑战赛的代码，比较值得一看(Code of Stanford University auto driving city challenge)

用python来爬取网络上的数据，本例通过BeautifulSoup，来爬当当网上感兴趣的书籍，将获取到的内容，保存在本地文件里面。