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.
Create a new console application
Add proper nuget packages
Manually add a .dll reference and copy said .dll to output
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.
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.