Accessing Azure for Free with BizSpark

Hello World!

As Azure becomes more and more popular and I encounter more startups, I find myself doing this tutorial all the time and explaining it.  Therefor, I have decided to write a blog article with pictures, to make my life (and yours) easier.

What is BizSpark

BizSpark is the best thing since sliced bread for a startup.  It is literally every development tool and license that Microsoft has to offer for free for commercial purposes for 3 years.  Not only that, but you get $150/month (as of this writing) in Azure for 3 years as well.  As if it couldn’t get any better, you get access to reduced pricing on various products from Microsoft Partners.  Microsoft being such a giant of a company, there are a TON of partners you get special pricing from.  BizSpark also includes product licensing such as just your simple windows licenses, or visual studio licenses, and even SQL Server licenses.  Its everything!  Usually at this point I get the question, so what’s the catch?  There is no catch!  Microsoft wants you to use their tools and be successful with their tools so that when you become a giant company, you are using their tools and not a competitors.  Therefor Microsoft gives these tools to high potential startups for free!  If you think you qualify, apply or come to an event I attend (usually found on the events tab).  You can also ping me on twitter @DavidCrook1988.

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How to Datamine Zillow

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As many of you may know at this point, I am relocating to South Florida.  Final location to be determined, but will probably be renting around Pompano Beach or Fort Lauderdale while working out of Venture Hive and the Microsoft Fort Lauderdale Offices.  So what does this have to do with Zillow?  Well, It has EVERYTHING to do with Zillow.  What I’ve found while searching for homes is that between Realtors, Zillow and Trulia, they really just don’t have a predictive analytics solution that works for me.  So I decided to give a shot at AzureML to mash together a few datasets to send me notifications more to my liking than is currently being sent.  So step 1 in this plan is to data mine Zillow.  Luckily, Zillow has an api for that.  Or if you are feeling particularly frisky, Zillow gets their data from ArcGIS (example for Raleigh).  So lets get cracking…

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Intro to Angular, Web API and Azure

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So I thought it would be beneficial to discuss Angular, Web API and Azure in some form of depth as well as provide an entire set of functioning code.  I will start by addressing a few things, What is Angular, What is Web API, and what is Azure?  Followed by the code and explanation of the code.  The code itself provides a simple website, which has restful routing, requests for processing and lists out data from a database acquired from said processing.

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So you want to be an Analytics Developer

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I get a series of questions all the time.

  1. How do I switch careers to be a developer?
  2. How do I become a data scientist?
  3. How do I add intelligence to my code?
  4. How do I get a job in distributed computing?
  5. How do I code more analytically?

The answer to these questions are pretty much all the same.  Step 1, learn about it and build one piece of software focused on that goal.  Step 2, go for it, just do it.  So that said, Microsoft has a fantastic resource, Microsoft Virtual Academy, which provides free training around various topics from entry level to advanced.  This article focuses on a learning plan with MVA to attain the goal of becoming an Analytics Developer.

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Mocking IoT Telemetry Data with Azure

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This should prove to be an interesting series of posts coming up, as I am working on a new project that is very unique and interesting. The idea is to use incoming data from Arduinos, Raspberry Pis, Gallileos, Edisons and other assortments of IoT type devices connected to oil and gas pipelines to determine if a leak is currently in progress and also predict if a leak is likely to occur in the future based on current and trending conditions.

My part in the project is all back end analytics, and I have very little to do with the actual telemetry and hardware. The telemetry will be posted using Azure Event Hubs, and thus my portion of the project begins with mocking that real time data at a large enough geo dispersed scale that I can develop a system that can handle it, and then switch my configurations to consume from the production event hubs. Since I am no longer a consultant working on projects with trade secrets and everything these days is about the elevation of skills in the community, I have posted everything on github that you can download and peruse at your leisure. Please note that this is in progress and well the github source may not necessarily work when you look. I’ll try to enforce a standard to comment “working – comment” on pushes to the repository. The git repository is located here: https://github.com/drcrook1/OilGas

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Adopting F#

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You can see from my blog that I have been increasing my adoption of F# and my love of the language is growing.  I find the language very conducive to cloud computing.  F# at its core seems to be built for distributed computing.  If you program with F# in an idiomatic way, you are setting yourself up for success on the cloud, as the cloud is a variably sized distributed system that you are deploying production code to.  That is what F# excels at.

As much as I have loved F#, it has not been all roses and sunshine.  There have been issues.  This article at its core is really an ask from the community to support me in building the case and evangelizing F# in such a way it can be recognized and adopted not only by the community, but by those who make the decisions to expend resources on additional tooling and support.  I must iterate that the contents of this article are in no way the opinion of Microsoft, but merely my own observations.  From these observations I have developed a strategy and action items that we the F# community must do to achieve these goals.

First, we must step outside of our normal mindset as F# developers and begin looking at the language from the outside perspective.  We must also look at some trends.

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Deploying F# Web Job to Azure

Hi All,

This article is one of those that is going to help remind me how to do this deployment, as it can be a bit tricky.  If you are working with F# for web jobs, like I have started doing, there are a few steps.

  1. Create a new console application
  2. Add proper nuget packages
  3. Manually add a .dll reference and copy said .dll to output
  4. Zip up and deploy entire output folder.

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Manage Azure Blobs with F#

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So you are going to notice a slight shift in this blog to start incorporating not only video game development, but hardcore data analytics.  As part of that shift, I am going to start incorporating F# into my standard set of languages as it is the language of hardcore data analytics if you roll with the .NET stack.

This particular article is about building a console based blob manager in F# instead of C#.  The very first thing I noticed about using F# to manage my blobs as opposed to C# is just the sheer reduction in lines of code.  The code presented here is a port of the C# article located here.  This code will eventually make its way into a production system which is part of a big data solution I am building.  New data sets that we acquire will be uploaded into blob storage, an entry stored into a queue, with a link to the data set.  Once a job is prepared to run, the data will be moved to Hadoop to do the processing and then stored in its final location.  So step 1 is…Store data in Blob storage.

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Understanding AzureML – Part 2: Binary Classification

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Welcome to Part 2!  We will be discussing Binary Classification.  So I hope many of you have started using AzureML.  If not, you should definitely check it out.  Here is the link to the dev center for it.  This article series will focus on a few key points.

  • Understanding the Evaluation of each Model Type.
  • Understanding the published Web Service of each Model

If you are looking for how to build a simple how to get started, check out this article.

The series will be broken down into a three parts.

Part 1: Regression

Part 2: Binary Classification

 

So lets get started!

AzureML

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