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资源列表
BP
- matlab BP神经网络学习示例，适合新手，共四个实例(A preliminary learning example of BP neural network)
RNN
- 利用MATLAB实现循环神经网络的例子，便于大家更好的理解循环神经网络RNN的原理。(The example of recurrent neural network is implemented by MATLAB, so that you can have a better understanding of the principle of recurrent neural network RNN.)
BP_net
- 齿轮箱故障诊断，用于诊断齿轮箱的几种不同的故障类型。(Fault diagnosis of gear box)
LDA1
- LDA线性判别算法，可以用来对数据进行降维(LDA linear discriminant algorithm can be used for dimensionality reduction of data.)
mnist98
- 改进的dnn，准确率达到了百分之98，有注释(The accuracy of the improved DNN is ninety-eight percent, with annotations)
pyDogVsCat
- 识别率85%，kaggle上有名的猫狗大战算法，可以很方便的查看分类结果。每一个epch需要22s左右（GTX1050Ti 4G）(The recognition rate is 85%. The famous dog and dog algorithm on kaggle is very convenient for us to see the classification results. Each epch needs about 22s (GTX1050Ti 4G))
lle
- lle用来处理高维数据降维，经检验此程序运行效果很好(LLE is used to deal with dimensionality reduction of high-dimensional data. It is proved that the program runs well.)
simpleCNN
- 在anaconda+opencv+tensorflow平台下，利用简单的CNN卷积神经网络进行手写字符识别(Under the anaconda+opencv+tensorflow platform, we use simple CNN convolution neural network to handwritten character recognition.)
CNN
- 手写体识别的训练，采用卷积神经网络，附带数据集下载代码(The training of handwritten recognition is based on convolution neural network, and the download from the dataset.)
万门大学强化学习算法代码RW模型+TD模型
- 万门大学，强化学习，rw模型算法代码实现， V(CS) = V(CS) + A * ( V(US) * us - V(CS) * cs ) td模型， V(s{t}) = V(s{t}) + a[R(t+1) + rV{S(t+1)} - V{S(t)}](In the intensive learning of the University of Wan men, the RW algorithm, the python implementation, the algorithm f
CS_SVM_exmp
- 该程序是cs-svm的程序，用于对svm的算法优化(This program is a program of cs-svm, which is used to optimize the algorithm of SVM.)
A_star
- 能够进行路径规划，用于全局路径规划，是目前较为广泛的全局路径规划算法(Can perform path planning for global path planning. It is currently a relatively extensive global path planning algorithm.)