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Machine-Learning-Tokyo/DL-workshop-series: Material used for Deep Learning relat ...

原作者: [db:作者] 来自: 网络 收藏 邀请

开源软件名称(OpenSource Name):

Machine-Learning-Tokyo/DL-workshop-series

开源软件地址(OpenSource Url):

https://github.com/Machine-Learning-Tokyo/DL-workshop-series

开源编程语言(OpenSource Language):

Jupyter Notebook 100.0%

开源软件介绍(OpenSource Introduction):

DL-workshop-series

Code used for Deep Learning related workshops for Machine Learning Tokyo (MLT)

Part I: Convolution Operations

Implementation

ConvKernels: colab notebook with simple examples of various kernels applied on an image using convolution operation ConvNets: colab notebook with functions for constructing keras models. Models:

  1. AlexNet
  2. VGG
  3. Inception
  4. MobileNet
  5. ShuffleNet
  6. ResNet
  7. DenseNet
  8. Xception
  9. Unet
  10. SqueezeNet
  11. YOLO
  12. RefineNet

Slides

Link to the presentation: https://drive.google.com/open?id=1sXztx3E9M3G0BIRLh6sxaqVOEOdJVJTrzHOixA5b-rM

Cheat Sheet: Alt text

Video series: CNN Architectures (including implementation)

YouTube Playlist

Part II: Learning in Deep Networks

YouTube Playlist




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