## Overview
MNIST Net is a tensorflow Mobile Net V2 model fine tuned for 28x28x1 MNIST Handwritten Digits Classification
The Images are internally rescaled in [0, 1] range and since Mobile Net V2 expects atleast 32x32 images, zero padding is added, also to translate the image to 3 color channels, we have used 1x1 Conv2D layer before the pretrained Mobile Net V2 layers
{}
keras region:us
TAGS
#keras #region-us 

## Overview
MNIST Net is a tensorflow Mobile Net V2 model fine tuned for 28x28x1 MNIST Handwritten Digits Classification
The Images are internally rescaled in [0, 1] range and since Mobile Net V2 expects atleast 32x32 images, zero padding is added, also to translate the image to 3 color channels, we have used 1x1 Conv2D layer before the pretrained Mobile Net V2 layers
## Overview
MNIST Net is a tensorflow Mobile Net V2 model fine tuned for 28x28x1 MNIST Handwritten Digits Classification
The Images are internally rescaled in [0, 1] range and since Mobile Net V2 expects atleast 32x32 images, zero padding is added, also to translate the image to 3 color channels, we have used 1x1 Conv2D layer before the pretrained Mobile Net V2 layers
TAGS
#keras #region-us 
 ## Overview
MNIST Net is a tensorflow Mobile Net V2 model fine tuned for 28x28x1 MNIST Handwritten Digits Classification
The Images are internally rescaled in [0, 1] range and since Mobile Net V2 expects atleast 32x32 images, zero padding is added, also to translate the image to 3 color channels, we have used 1x1 Conv2D layer before the pretrained Mobile Net V2 layers
passage: TAGS
#keras #region-us 
## Overview
MNIST Net is a tensorflow Mobile Net V2 model fine tuned for 28x28x1 MNIST Handwritten Digits Classification
The Images are internally rescaled in [0, 1] range and since Mobile Net V2 expects atleast 32x32 images, zero padding is added, also to translate the image to 3 color channels, we have used 1x1 Conv2D layer before the pretrained Mobile Net V2 layers