https://github.com/jyni16/deeplearning-beginner

Various Classical Deep-learning Algorithm coded by Tensorflow and Pytorch framework
https://github.com/jyni16/deeplearning-beginner

alexnet-model deep-learning pytorch-tutorial resnet-34 softmax-regression tensorflow tensorflow-tutorials

Last synced: 7 days ago
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Various Classical Deep-learning Algorithm coded by Tensorflow and Pytorch framework

• Host: GitHub
• URL: https://github.com/jyni16/deeplearning-beginner
• Owner: JYNi16
• Created: 2022-07-14T05:22:27.000Z (about 2 years ago)
• Default Branch: master
• Last Pushed: 2022-09-23T15:28:36.000Z (about 2 years ago)
• Last Synced: 2024-09-23T07:33:31.421Z (11 days ago)
• Topics: alexnet-model, deep-learning, pytorch-tutorial, resnet-34, softmax-regression, tensorflow, tensorflow-tutorials
• Language: Python
• Homepage:
• Size: 161 KB
• Stars: 13
• Watchers: 1
• Forks: 4
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Classical-Deeplearning-Algorithm

Various Classical Deep-learning Algorithm coded by Tensorflow and Pytorch framework, respectively.

Requirements:

1. Pytorch 

2. Tensorflow 2.X 

3. Numpy

Contents:

1. Linear Regression(coded by numpy and pytorch, respectively)

2. Softmax Regression(coded by Pytorch)

3. LeNet (using mnist dataset, coded by tensorflow)

4. AlexNet (using cifar-10 dataset, coded by tensorflow)

5. ResNet (using cifar-10 dataset, coded by tensorflow)

6. Self-defined dataset in tensorflow input pipline (binary classification)

7. Funetuning_tf funetuing training use vgg16 pretrained net-work (coded by tensorflow)

8. Funetuning_torch funetuing training use alexnet pretrained net-work (coded by pytorch)