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说明：  在python中实现xgboost模型的训练集预测(train a xgboost model and make prediction in Python)

最优化方法之近端梯度下降法，适用于L1正则项的最优化。(Proximal gradient descent)

说明：  几个python的计算例子，关于数据的处理，对初学者有用。(Several python calculation examples, data processing, useful for beginners.)

【实例简介】

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.)

说明：  TensorFlow实战代码配套书的源程序(source code for TensorFlow actual combat code pdf)

基于树莓派B+版本的车牌识别设计，辨识部分以树莓派3B+/3B为核心处理器，基于Linux平台，通过python3.5和OpenCV来对含有车牌信息的图片，进行高斯去噪、灰度化、边缘检测、二值化、闭操作、字符分割、字符识别匹配等一系列图像处理操作最终实现车牌识别这个系统。(Based on the design of license plate recognition of raspberry pie B+version, the recognition part takes raspberry pie 3B+/3B as the core processor, and based on Linux platform, uses Python 3.5 and OpenCV to process the image containing license plate information, and carries out a series of image processing operations such as Gaussian denoising, graying, edge detection, binarization, closed operation, character segmentation, character recognition matching, etc. Finally, the system of license plate recognition is realized)

GMM聚类实现，利用jupybook实现出来，可以看算法的实现原理。(GMM clustering implementation, using jupybook realization, can see the implementation principle of the algorithm.)

基于matplotlib在python中绘制图形。代码中给出了一个sinx，一个三维曲面的绘制代码示例。

英文教材：《深入浅出，使用python编程》(python learning in English)