分享一下我老师大神的人工智能教程！零基础，通俗易懂！http://blog.csdn.net/jiangjunshow
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0. alexnet 工具箱下载
下载地址：Neural Network Toolbox(TM) Model for AlexNet Network
- 需要先注册（十分简单），登陆，下载；
- 下载完成之后，windows 是无法运行该文件的；
- 需要打开 matlab，进入到该文件所在的路径，双击运行；（注：需要较久的时间下载安装 alexnet）
1. demo（十一行代码）
deep-learning-in-11-lines-of-matlab-code
clearcamera = webcam;nnet = alexnet;while true picture = camera.snapshot; picture = imresize(picture, [227, 227]); label = classify(nnet, picture); image(picture); title(char(label));end
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2. 网络结构
>> nnet = alexnet;>> nnet.Layers1 'data' Image Input 227x227x3 images with 'zerocenter' normalization2 'conv1' Convolution 96 11x11x3 convolutions with stride [4 4] and padding [0 0]3 'relu1' ReLU ReLU4 'norm1' Cross Channel Normalization cross channel normalization with 5 channels per element5 'pool1' Max Pooling 3x3 max pooling with stride [2 2] and padding [0 0]6 'conv2' Convolution 256 5x5x48 convolutions with stride [1 1] and padding [2 2]7 'relu2' ReLU ReLU8 'norm2' Cross Channel Normalization cross channel normalization with 5 channels per element9 'pool2' Max Pooling 3x3 max pooling with stride [2 2] and padding [0 0]10 'conv3' Convolution 384 3x3x256 convolutions with stride [1 1] and padding [1 1]11 'relu3' ReLU ReLU12 'conv4' Convolution 384 3x3x192 convolutions with stride [1 1] and padding [1 1]13 'relu4' ReLU ReLU14 'conv5' Convolution 256 3x3x192 convolutions with stride [1 1] and padding [1 1]15 'relu5' ReLU ReLU16 'pool5' Max Pooling 3x3 max pooling with stride [2 2] and padding [0 0]17 'fc6' Fully Connected 4096 fully connected layer18 'relu6' ReLU ReLU19 'drop6' Dropout 50% dropout20 'fc7' Fully Connected 4096 fully connected layer21 'relu7' ReLU ReLU22 'drop7' Dropout 50% dropout23 'fc8' Fully Connected 1000 fully connected layer24 'prob' Softmax softmax25 'output' Classification Output cross-entropy with 'tench', 'goldfish', and 998 other classes
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给我老师的人工智能教程打call！http://blog.csdn.net/jiangjunshow
