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A set of educational deep learning demos applied to the MNIST dataset

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# deepnumbers
A set of educational deep learning demos applied to the MNIST dataset

## Slides

You can find a presentation about this work at:  
https://www.slideshare.net/natalinobusa/7-steps-for-highly-effective-deep-neural-networks

Hires pdf available here:
https://drive.google.com/file/d/0BwNrPuGaMi8PbVhUYUVKWUhGRjQ

## Brighttalk
I do have a webinar on this one, thanks to the folks at Brighttalk.  
Check https://www.brighttalk.com/webcast/8251/252545

## Youtube
I thinking of taking screen captures of this project and posting it on youtube. So far my attempts have not been super successful (kudos to those pro youtubers out there - it's *definitely* not as easy as it looks).

## Regression

## SLP

 <img src="https://github.com/natbusa/deepnumbers/blob/master/images/slp.png?raw" alt="slp mnist"/>
 <img src="https://github.com/natbusa/deepnumbers/blob/master/images/biology.png?raw" alt="ann biology"/>

## MLP

 <img src="https://github.com/natbusa/deepnumbers/blob/master/images/supervised.png?raw" alt="supervised ann"/>

## Convolutional

 <img src="https://github.com/natbusa/deepnumbers/blob/master/images/convblocks.png?raw" alt="conv elements"/>
 <img src="https://github.com/natbusa/deepnumbers/blob/master/images/convnet.png?raw" alt="convnet"/>

## Batch Normalization

 <img src="https://github.com/natbusa/deepnumbers/blob/master/images/batchnorm.png?raw" alt="batch normalization"/>

## Inception

 <img src="https://github.com/natbusa/deepnumbers/blob/master/images/inception.png?raw" alt="inception"/>

## Residual

 <img src="https://github.com/natbusa/deepnumbers/blob/master/images/resnet.png?raw" alt="residual networks"/>

## LSTM on images

 <img src="https://github.com/natbusa/deepnumbers/blob/master/images/lstm.png?raw" alt="lstm on images"/>

deepnumbers

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