Python and OpenCV for starter

说明：  强化学习可以按照方法学习策略来划分成基于值和基于策略两种。而在深度强化学习领域将深度学习与基于值的Q-Learning算法相结合产生了DQN算法，通过经验回放池与目标网络成功的将深度学习算法引入了强化学习算法。(Reinforcement learning can be divided into value-based learning and strategy based learning according to method learning strategies. In the field of deep reinforcement learning, dqn algorithm is generated by combining deep learning with value-based Q-learning algorithm. Through experience playback pool and target network, deep learning algorithm is successfully introduced into reinforcement learning algorithm.)

将ARCGIS的MXD文件转换为PDF的python代码。(A simple tool to convert multiple map documents into a multi-page PDF document. This script will export multiple map document layoutinto a single # output PDF file. The script is intended to run within a script tool. There are two # parameters: # 1) Select Map Documents to Append, # 2) Output PDF.)

说明：  通过Python，Theano和Tensorflow，掌握数据科学和机器学习(Master Data Science and Machine Learning with Modern Neural Networks written in Python, Theano, and TensorFlow)

python的打外星人游戏，包含主程序，几个类，图片和game_function几个文件

说明：  调用标定好的双目摄像机，利用其内外参数进行立体匹配，计算所拍图像的视差，产生深度图(Call the calibrated binocular camera, use its internal and external parameters for stereo matching, calculate the parallax of the captured image, and generate depth map)

分词方法总体上分为两类，一是非基于词典的分词，相当于人工智能领域计算。一般用于机器学习，特定领域等方法，这种在特定领域的分词可以让计算机在现有的规则模型中，推理如何分词，精确度较高，实现相对复杂。二是基于词典的分词，是最常见的分词方法，具体算法有正向最大匹配法（FMM）、逆向最大匹配法（RMM）和双向最大匹配法（BM）。本文在学习正向最大匹配算法的同时，用Python进行分词实现。本文使用的是 请点击左侧文件开始预览 ！预览只提供20%的代码片段，完整代码需下载后查看 加载中 侵权举报

Python算法学习入门资料，中文版，学习Python的入门经典(Python algorithm learning materials)

说明：  rbm受限玻尔兹曼机的python代码，总共有5种写法，总有一款适合你(Restricted Boltzmann machine python code,5 files in total, which can be run)

python机器学习算法实战里KNN 算法代码。

通过网络爬虫方法，使用python与selenium联合，加载chrome引擎，对企业工商数据进行收集整理