资源列表
EM Algorithm
- 通过使用EM算法来实现混合高斯的分类,有比较好的效果，很直观的可以展示，对于初学者很有帮助(Through the use of EM algorithm to achieve the classification of mixed Gaussian, have better results, very intuitive to display, helpful for beginners)
predict_Bayesian Network
- 贝叶斯网络预测篮球队胜负，使用了爬山学习算法(The Bias network predicts the winning and negative of the basketball team and uses the mountain climbing algorithm.)
nn_classification
- 使用单隐层神经网络进行二分类 使用python语言，先生成一个数据集，无法（但尝试）用logistic回归对数据集进行二分类，最后使用单隐层神经网络对数据集进行分类(classify a dataset with a 3-dimensional hidden layer)
dbn
- 本程序是用python写的一个深度学习程序，该程序基于限制性玻尔兹曼机实现了深度信念网络。(This procedure is a deep learning program written in python, the program based on the limited Boltzmann machine to achieve a depth of faith network.)
yuqun
- 人工智能鱼群算法，非常好的一个基础的代码，萨达十大沙发沙发上(Artificial intelligence fish swarm algorithm)
knn
- python语言编写的，利用KNN实现分类以及梯度下降算法。(Use kNN to classify)
pso
- 标准pso算法的MATLAB平台实现，应该可以用吧(Standard pso algorithm MATLAB platform, you should be able to use it)
kNN
- kNN金陵算法算法源文件，包括输入，过程逻辑算法，输出(Algorithm source file)
nn_CIFAR.py
- pytorch tutorial 代码 简单神经网络 数据集CIFAR(pytorch nn training sample code, Dataset: CIFAR dataset Usage: python3 nn_CIFAR.py)
feed
- 结合模糊评价和bp神经网络将网路权值转换成个因素的权重 Combining fuzzy evaluation and BP neural network to transform the weights of network weights into factors(Combining fuzzy evaluation and BP neural network to transform the weights of network weights into factors)
reinforement.tar
- 强化学习grid python代码，使用的算法为动态规划，很好的入门强化学习的例子(reinforement grid study.)
ANN_fitting_example_1
- ANN fitting，使用多层神经网络对某一个函数进行插值逼近，建立代理模型(ANN fitting. Using a multi-layer neural network to interpolate a certain function to establish a proxy model)