▍1. LRR
低秩表达程序，MATLAB. Robust Subspace Segmentation by Low-Rank Representation(Low-Rank Representation program, MATLAB Robust Subspace Segmentation by Low-Rank Representation)
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▍2. knn_svm_tree
说明： 对于iris数据集的knn、svm、决策树算法分类的简单实现(Simple implementation of KNN, SVM and decision tree algorithm classification for iris dataset)
▍3. Spark机器学习源码
说明： Spark 机器学习代码，有大量机器学习算法实例。(Spark machine learning code, there are a large number of machine learning algorithm examples.)
▍4. 587244
matlab数值积分工具箱 nit toolbox(Matlab numerical integration toolbox nit toolbox)
▍6. GeoQ_Spider
通过PYTHON编写的爬虫程序，爬取Geoq的人口密度数据(The population density data of Geoq is crawled by a crawler program written in PYTHON)
▍7. GeoQ_Spider
说明： 通过PYTHON编写的爬虫程序，爬取Geoq的人口密度数据(The population density data of Geoq is crawled by a crawler program written in PYTHON)
▍8. ZookeeperClient
zookper节点搭建、持久节点、临时节点创建以及动态上下线(Construction of Zookper Node and Dynamic Up and Down)
▍9. ZookeeperClient
说明： zookper节点搭建、持久节点、临时节点创建以及动态上下线(Construction of Zookper Node and Dynamic Up and Down)
▍11. ID3算法的改进
说明： 在Weka平台运行的ID3算法，对普通的ID3算法做了一点改进，有四个不同的改进，对应了四个不同的算法，适合实验报告和课程报告。直接可以运行，无需调试。(The ID3 algorithm running on the Weka platform has made a little improvement on the ordinary ID3 algorithm. There are four different improvements, corresponding to four different algorithms, which are suitable for experiment reports and course reports. It can run directly without debugging.)
▍13. StockPricePrediction-master
python深度学习股票分析框架，就这么多了(python learning stock)
▍14. StockPricePrediction-master
说明： python深度学习股票分析框架，就这么多了(python learning stock)
▍15. 深度学习之TensorFlow：入门、原理与进阶实战
该压缩文件是《深度学习之Tensorflow的入门、原理及进阶实战》，里面讲述了如何搭建TensorFlow环境，并讲述了深度学习的一些理论基础知识，而且通过例子进行辅助，能更好的理解掌握。(The compressed file is "Introduction, Principle and Advanced Combat of Tensorflow for Deep Learning", which describes how to set up the TensorFlow environment, and describes some theoretical basic knowledge of deep learning, and assists with examples to better understand .)
▍16. 深度学习之TensorFlow：入门、原理与进阶实战
说明： 该压缩文件是《深度学习之Tensorflow的入门、原理及进阶实战》，里面讲述了如何搭建TensorFlow环境，并讲述了深度学习的一些理论基础知识，而且通过例子进行辅助，能更好的理解掌握。(The compressed file is "Introduction, Principle and Advanced Combat of Tensorflow for Deep Learning", which describes how to set up the TensorFlow environment, and describes some theoretical basic knowledge of deep learning, and assists with examples to better understand .)
▍17. 利用BP神经网络进行字符识别
利用神经网络进行字符的识别，并对神经网路训练(Use neural networks for character recognition and neural network training)
▍18. Wcntent-solve
用VB实现数值积分的算法集,包括梯形求积法,反常积分,三重积分,龙贝格方法,辛卜生方法等6种方法,(VB is used to realize the algorithm set of numerical integration, including trapezoidal quadrature method, anomalous integral, triple integral, Romberg method, Simbsen method and so on.)
▍19. Python-for-Finance-Second-Edition-master
Python是一种面向对象、解释型计算机程序设计语言，其应用领域非常广泛，包括数据分析、自然语言处理、机器学习、科学计算以及推荐系统构建等。 本书用Python语言来讲解算法的分析和设计。本书主要关注经典的算法，但同时会为读者理解基本算法问题和解决问题打下很好的基础。(Python is an object-oriented, interpretive computer programming language. It has a wide range of applications, including data analysis, natural language processing, machine learning, scientific computing and recommendation system construction. This book uses Python language to explain the analysis and design of algorithms. This book focuses on classical algorithms, but at the same time it will lay a good foundation for readers to understand basic algorithms and solve problems. The book consists of 11 chapters. The tree, graph, counting problem, inductive recursion, traversal, decomposition and merging, greedy algorithm, complex dependency, Dijkstra algorithm, matching and cutting problem, difficult problem and its dilution are introduced. The book has exercises and reference materials at the end of each chapter, which provides readers with more convenience for self-examination and further stu)
▍20. Xztration-Multicondition-Research
运筹学大作业：实现多条件最大运筹与最小运筹的最佳方案计算与价值预测(Operational Research Big Operation: the Best Scheme calculation and value Prediction for realizing Multi-condition maximum and minimum operational Research)
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