Apparently Amazon has a Deep Learning AMI which includes MXNet, Caffe, Tensorflow, Theano, and Torch.

Here’s a getting started with mxnet

# This seems to have the latest image...    
docker run -it kaixhin/mxnet



Cool example..

import mxnet as mx
a = mx.sym.Variable('a')
b = mx.sym.Variable('b')
c = a + b
assert a.name == "a", "Symbol name incorrect."
assert b.name == "b", "Symbol name incorrect."
(a, b, c)


# elemental wise times
d = a * b  
# matrix multiplication
e = mx.sym.dot(a, b)   
# reshape
f = mx.sym.Reshape(a, shape=(2,6))  
# broadcast
g = mx.sym.broadcast_to(f, shape=(3,2,6))  

# Output may vary
net = mx.sym.Variable('data')
net = mx.sym.FullyConnected(data=net, name='fc1', num_hidden=128)
net = mx.sym.Activation(data=net, name='relu1', act_type="relu")
net = mx.sym.FullyConnected(data=net, name='fc2', num_hidden=10)
net = mx.sym.SoftmaxOutput(data=net, name='out')
mx.viz.plot_network(net, shape={'data':(100,200)})


img