MXNet review: Amazon's scalable deep learning

Amazon’s favorite deep learning framework scales across multiple GPUs and hosts, but it's rough around the edges

Become An Insider

Sign up now and get FREE access to hundreds of Insider articles, guides, reviews, interviews, blogs, and other premium content. Learn more.
At a Glance
  • MXNet v0.7

    InfoWorld Rating
    Learn more
    on Distributed Machine Learning...

Deep learning, which is basically neural network machine learning with multiple hidden layers, is all the rage—both for problems that justify the complexity and high computational cost of deep learning, such as image recognition and natural language parsing, and for problems that might be better served by careful data preparation and simple algorithms, such as forecasting the next quarter’s sales. If you actually need deep learning, there are many packages that could serve your needs: Google TensorFlow, Microsoft Cognitive Toolkit, Caffe, Theano, Torch, and MXNet, for starters.

I confess that I had never heard of MXNet (pronounced “mix-net”) before Amazon CTO Werner Vogels noted it in his blog. There he announced that in addition to supporting all of the deep learning packages I mentioned above, Amazon decided to contribute significantly to one in particular, MXNet, which it selected as its deep learning framework of choice. Vogels went on to explain why: MXNet combines the ability to scale to multiple GPUs (across multiple hosts) with good programmability and good portability.

To continue reading this article register now