[#VS2015] #MachineLearning and Visual Studio? 3 platforms for a quick start

Hello!

When you create apps using Arduino, Galileo or any of these platforms, the amount of data that you can generate is quite big. Yesterday I wrote a post where I commented an almost real example, about how the information on the consumption habits of a person and a series of connected devices can be the basis for the exploitation of these data in a Machine Learning platform.

Personally one of them that I use most is Azure Machine Learning, about which I have pending write some posts. AzureML is very complete, and a Getting Started of this type opens the mind in a few minutes. That Yes, it’s time to add a new language to your skills: “Welcome to R“. By now RStudio is the ideal tool for programming in R.

If you want something closer and simple, there are several options available that allow us to be within “the comfort of Visual Studio“. Here I have 2 options.

Numl, of Seth Juarez, is one of them. It is available for download as a package NuGet and the great Juan María Hernández (@gulnor) has presented it in an amazing post, “Machine Learning and Disney Princesses“. Numl relies on a supervised learning and the truth that Seth resolves it in a very elegant manner.

Bonus Track: Seth last year gave a talk of interesting ML which can be seen on Channel 9 (link)

Another option is Accord.Net Framework. This has an interesting history. If you’ve worked with image processing, as surely you know AForge.Net. As well, Accord.Net is based largely on the algorithms of AForge. Numl, as there is a very simple and useful getting started. In this case the examples we have also other issues such as processing of audio and images and statistics.

Important: Care, that this library used originally Google Code and… because now not da more service. Have moved all those sources to Github, although still there are references and results of searches that we carry to Google Code.

As well, not have an excuse for not starting to put you in the fabulous world of ML!

Greetings @ Home

/El Bruno

Sources

Machine Learning, http://en.wikipedia.org/wiki/Machine_learning

R Programming Language, http://www.r-project.org/

Azure Machine Learning, http://azure.microsoft.com/en-us/services/machine-learning/

Machine Learning con princesas Disney, http://blog.koalite.com/2015/03/machine-learning-con-princesas-disney/

Numl, https://github.com/sethjuarez/numl

Architecting Predictive Algorithms for Machine Learning, http://channel9.msdn.com/events/TechEd/Europe/2014/CDP-B240

Accord.Net Framework, http://accord-framework.net/

Accord.Net Framework Samples, https://github.com/accord-net/framework/wiki/Sample-applications