资源列表
BP-network
- 机器学习20讲之BP神经网络源码,含手写数据库-the code of BP network for 20 section machine learning
cnn
- 卷积神经网络是近年来广泛应用于模式识别、图像处理等领域的一种高效识别算法,它具有结构简单、训练参数少和适应性强等特点。-Convolutional Neural Network Library
Knn
- Knn源码,k最邻近方法,是一种统计分类器,属于惰性学习,对于包含数据特征变量筛选尤其有效-Knn source, k nearest neighbor method is a statistical classifier learning are inert, it contains the data for the characteristic variable filter is especially effective
code
- 卷积深度置信网,在Lee的基础上进行了一定的完善,使用RBM来预训练CNN,实现对CNN的初始化-Convolutional neural nets
NN
- batch normalization在神经网络上的实现-batch normalization implemented on Neural Networks
CNN
- 深度学习中卷积神经网络,实现手写数字的分类,其中包含网络的初始化,训练,测试三个模块。包含mnist_uint8.mat文件,CNN入门学习程序。-Convolution depth study neural networks, digital handwritten classification, which includes the network initialization, training, testing three modules. Files contain mnist_uin
c2
- 人工神经网络,机器学习,以及混沌神经网络的ppt-Artificial neural networks, machine learning, and chaotic neural network based on ppt
python-2.6.6
- python2.6-6安装文件,用于使用libsvm的.py文件。-installation file of python
DeepLearnToolbox-master
- matlab中深度学习工具箱,具有备注,方便易懂(Matlab in-depth learning toolbox, with notes, easy to understand)
MovieSite
- 利用kmeans对电影进行聚类,利用java实现-Use kmeans clustering of the film, using java to achieve
DEEP-CNN
- matlab下的CNN代码,有小例子供参考(the CNN code, there are small examples for reference)
DeepLearnToolbox-master
- DNN工具包,可以利用MATLAB实现深度神经网络。达到预测的目的(DNN toolkit can implement deep neural network using MATLAB. Achieve the purpose of prediction)