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The ever growing internet of things provides expanding opportunities for software engineers to leverage their skills. If you are not writing software for the devices themselves there are still ample opportunities to build backend systems to capture and analyze the avalanche of data that these devices produce.  In this post we will be looking at creating a backend system for capturing connected device data for a hypothetical IOT device. We will be using Python and a lightweight framework called Flask to create a REST based endpoint that our device calls to submit location data. Our service will store its data in a NOSQL repository powered by Azure Cosmos DB. You can find the repository for this post here . One of the big trends in software engineering is the rising popularity of Python. This multipurpose language has a dominant position in the machine learning space. If you are looking to build some skills in Python but are not currently working on a machine learning project you...

Python Machine Learning In Azure ML Studio Just quick post to show you how easy it is to migrate Jupyter notebooks into azure machine learning studio.    For this walkthrough we will use the preview of the latest release of ML Studio ( https://ml.azure.com/ ).    Microsoft has been hard at work making their Machine Learning Studio easier to use and the preview release has simplified several processes. When you bring up Azure ML Studio Importing a Jupyter notebook is a straight forward process.    Once you’ve loaded studio select notebooks and then select the upload files link. Once you have uploaded the file you’ll be able to select it and view it but no run it yet. We can’t run the uploaded notebook yet because we need to setup a VM that will be used process our data. Allowing you to control the size of the VM that your notebook will run on lets you control costs associated with housing the notebook in Azure.  Additionally, you can s...