Skip to content

JYNi16/Deeplearning-Beginner

Repository files navigation

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)

Releases

No releases published

Packages

No packages published

Languages