Machine-Learning-Tokyo/DL-workshop-series
Material used for Deep Learning related workshops for Machine Learning Tokyo (MLT)
| repo name | Machine-Learning-Tokyo/DL-workshop-series |
| repo link | https://github.com/Machine-Learning-Tokyo/DL-workshop-series |
| homepage | |
| language | Jupyter Notebook |
| size (curr.) | 11455 kB |
| stars (curr.) | 714 |
| created | 2018-11-23 |
| license | Apache License 2.0 |
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:
- AlexNet
- VGG
- Inception
- MobileNet
- ShuffleNet
- ResNet
- DenseNet
- Xception
- Unet
- SqueezeNet
- YOLO
- RefineNet
Slides
Link to the presentation: https://drive.google.com/open?id=1sXztx3E9M3G0BIRLh6sxaqVOEOdJVJTrzHOixA5b-rM
Cheat Sheet: 
Video series: CNN Architectures (including implementation)
Part II: Learning in Deep Networks
