Another data point on Anaconda from microsoft's Azure ML team - we've been using Anaconda for the past few years and have been very happy with it. One key feat

Another data point on Anaconda from microsoft's Azure ML team - we've been using Anaconda for the past few years and have been very happy with it. One key feature we like is that we can deploy a nearly identical suite of pkgs on Windows, Linux and MacOS w/o having to worry about mismatched versions, installation/update issues, etc. Case in point - the Azure ML Jupyter notebooks run on a farm of Linux/docker machines: https://blogs.technet.microsoft.com/machinelearning/2016/02/10/python-notebooks-in-the-cortana-analytics-gallery/ https://blogs.technet.microsoft.com/machinelearning/2016/02/... Once a model is built, it can be deployed for production/scale to the Azure ML backend which runs entirely on a farm of Windows machines. Both environments have matching Anaconda distros running underneath which makes running on two different OS's practically a non-issue. In fact 95% of our users probably have no idea their notebooks & production site run two OS's (in large part thanks to Python, Linux, Docker, Anaconda, ... and lots of other great open source software).