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DL-workshop-series

用于东京机器学习 (MLT) 深度学习相关研讨会的材料。「Material used for Deep Learning related workshops for Machine Learning Tokyo (MLT)」

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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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Overview
Name With OwnerMachine-Learning-Tokyo/DL-workshop-series
Primary LanguageJupyter Notebook
Program languageJupyter Notebook (Language Count: 1)
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License:Apache License 2.0
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Created At2018-11-23 02:05:44
Pushed At2023-12-20 01:35:58
Last Commit At2023-12-20 10:35:58
Release Count0
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Watchers Count66
Fork Count253
Commits Count138
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Issue Open Count1
Pull Requests Count2
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