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Implement five classic convolutional neural networks—LeNet, AlexNet, VGGNet, InceptionNet, and ResNet—using TensorFlow 2.8.

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tensorflow2.x-ex

Based on tensorflow2.8

pip install tensorflow==2.8.0 -i https://pypi.doubanio.com/simple/ py source code and FASHION_FC, MNIST_FC dataset download https://pan.baidu.com/s/19XC28Hz_TwnSQeuVifg1UQ Extraction code: mocm mkdir dataset Store dataset

1 Common functions

2 Use of datasets

3 Single-layer neural network

Single-layer neural network construction and SGD SGDM RMSprop Adam gradient descent algorithm

4 Neural network optimization

Regularization reduces overfitting, exponential decay accelerates learning rate

5 Build neural network eight-part

iris\MNIST\Fashion dataset

6 Neural network eight-part supplement

Self-made dataset Data enhancement Breakpoint continuous training Parameter extraction Drawing object recognition

7 Convolutional neural network construction

Building example Implement five classic convolutional networks: LeNet, AlexNet, VGGNet, InceptionNet, and ResNet

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Implement five classic convolutional neural networks—LeNet, AlexNet, VGGNet, InceptionNet, and ResNet—using TensorFlow 2.8.

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