This is for people preparing to attend my talk on Deep Learning at DataWorks Summit Berling 2018 (https://dataworkssummit.com/berlin-2018/#agenda) on Thursday April 19, 2018 at 11:50AM Berlin time. Many people are using IBM's excellent DSX platform which uses Jupyter Notebooks and the ever popular Kubernetes. I wanted to try out Apache MXNet in this environment. It's great. Create or reuse an existing notebook. For Python, the default is Jupyter. Zeppelin is now also supported. I am using Python 2.7 with DSX Desktop on an OSX workstation. This supports Apache MXNet. My local Apache MXNet installation and MXNet python installation worked well with DSX. I needed OpenCV for this example, so I was able to install right inside IBM DSX via !pip install --user opencv-python. Very easy to start a notebook and add your code, you get nice syntax coloring. I uploaded the precompiled model Here we can check our list of Python libraries with !pip list --isolated --format=columns. Very easy to run your Apache MXNet code right in a notebook. Easy to share with other data scientists and engineers in your group and others. IBM DSX Assets You will need to download the pre-built Inception model and add that to assets. synset.txt Inception-BN-0000.params Inception-BN-symbol.json See: https://mxnet.incubator.apache.org/tutorials/embedded/wine_detector.html curl --header 'Host: data.mxnet.io' --header 'User-Agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10.11; rv:45.0) Gecko/20100101 Firefox/45.0' --header 'Accept: text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8' --header 'Accept-Language: en-US,en;q=0.5' --header 'Referer: http://data.mxnet.io/models/imagenet/' --header 'Connection: keep-alive' 'http://data.mxnet.io/models/imagenet/inception-bn.tar.gz' -o 'inception-bn.tar.gz' -L curl http://data.mxnet.io/models/imagenet/synset.txt More Models http://data.mxnet.io/models/imagenet/ Source Code https://github.com/tspannhw/mxnet-in-notebooks https://github.com/tspannhw/ApacheBigData101
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