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Azure Machine Learning

Welcome to an internship at endjin!

by Ed Freeman

A career in software engineering doesn’t need to start with a Computer Science degree. The underlying traits of problem solving, a willingness to learn and the ability to collaborate well can be built in any field. Internships provide a great way to get your foot-in-the-door in the professional world, and arm you with some real-life experience for future endeavours. This post describes an internship at endjin, including the type of work you could be asked to do and what you could learn.

Automated R Deployments in Azure

by Jess Panni

It’s been great to see Microsoft embracing the R language on Azure, being able to easily operationalize R assets is changing the way organisations think about their analytical workloads. While it is trivial to publish an R model as a web service in Azure Machine Learning, there is still no easy way to integrate this […]

A short while ago, I was trying to classify some data using Azure Machine Learning, but the training data was very imbalanced. In the attempt to build a useful model from this data, I came across the Synthetic Minority Oversampling Technique (SMOTE), an approach to dealing with imbalanced training data. This blog describes what I […]

Azure data services part 3: Azure Machine Learning

by Alice Waddicor

In parts 1 and 2 of this mini-series, I wrote brief intros to HDInsight and Stream Insight, Azure’s offerings for big data analytics and real-time analytics. Next up, Azure Machine Learning. What it’s for: Azure Machine learning provides a GUI with drag and drop pre-built components for carrying out predictive analytics. You can also plug […]