How to train and deploy deep learning at scale

#artificialintelligence 

In five lines, you can describe how your architecture looks and then you can also specify what algorithms you want to use for training. There are a lot of other systems challenges associated with actually going end to end, from data to a deployed model. The existing software solutions don't really tackle a big set of these challenges. For example, regardless of the software you're using, it takes days to weeks to train a deep learning model. There's real open challenges of how to best use parallel and distributed computing both to train a particular model and in the context of tuning hyperparameters of different models.

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