Open Stack

Dear storleters,
As the deadline approaches I was thinking about the following idea:

End-to-End deep learning with OpenStack Storlets

Imagine that you have a huge dataset from which you could extract  
information using machine learning algorithms. The problem is that  
datasets usually need to go through a long and tedious curing and  
pre-processing before they can be 'presented' to machine learning  
algorithm. With large dataset this can get really painful. In this  
talk we present how storlets can be used to do an end-to-end  
supervised deep learning, thus processing all the data 'in-place'  
saving huge amounts of BW. As an example We show face recognition that  
starts with off-the-camera jpegs. This involves the following steps:

1. find the face bounding box
2. extract the face part
3. resize to a pre-defined resolution
4. change to greyscale
5. transform into a matrix that can be presented to a learning algorithm
6. train the algorithm over a large training set

We show that all steps can be done using storlets from within a  
Jupyter notebook.


Anyone who is interested in taking part please let me know.
Also, this is just an initial suggestion, feel free to suggest other  
examples or ideas.

Best,
Eran