资源列表
博弈论.tar
- 包含博弈论的基本概念和基本说明，对大家学习很有帮助(Basic concepts of game theory)
coherence-breaking
- 产生高斯型随机粗糙表面,参考文献 国防科技大学博士论文 《太赫兹目标散射特性关键技术研究 》(generate Gauss randon surface)
python_self
- 实现了机器学习的各种分类算法，如：knn，svm，朴素贝叶斯，神经网络，决策树等。(Various classification algorithms of machine learning, KNN, SVM, naive bayes, neural network, decision tree, etc.)
SVM
- 基于python的svm分类学习。线性可分svm，非线性svm。 对花卉（花蕾）进行分类，并可视化(SVM classification learning based on Python)
Regression
- python回归分析。利用花卉（花蕾）数据，进行python的回归分析学习。(regression analysis based on python)
Tacotron-2-master
- 机器学习,人声训练,老外编译好的东西，不错，可以学习一下下(Machine learning, voice training, foreigner compiled things, yes, you can learn about it.)
GAMS
- 最优潮流计算opf，内点法计算发电机成本(OPF,Optimal power flow calculation OPF, internal point method to calculate generator cost)
Generalised-Side-Lobe-Canceller-master
- 麦克风阵列处理-GSC（Generalized Sidelobe Canceller，广义旁瓣相消器）(GSC Generalized Sidelobe Canceller audio)
第14章
- 二维热传导方程有限差分法的MATLAB实现(matlab to achieve the two-dimensional parabolic equations Programming in matlab program for solving two-dimensional parabolic equation: TDE)
算法图解.pdf
- python的算法入门不错的书，生动有趣，适合要学习算法的人(Python algorithm entry good book)
gaussianprocess4Clas
- 用高斯过程的实现分类和回归的Matlab代码(Matlab code for implementing four classification and regression using Gauss process)
GBDT+SVM
- 使用机器学习中的SVM，GBDT算法构建分类模型，做分类预测。并且对测试结果评估，模型保存。(Use SVM and GBDT algorithm in machine learning to build classification model and do classification prediction. And evaluate the test results and save the model.)