Tag Archives: Azure ML

TDSP Lifecycle – Wrap-up

Microsoft in the News   Today’s installment is all about a not-so-new buzzword(s):  Intelligent Edge. The Intelligent Edge refers to a place, like the cutting edge.  The Intelligent Edge is where the action is.  This can refer to the smart watch on your wrist, a sensor placed in a vineyard, a monitor under the hood […]

TDSP Lifecycle – Client Acceptance

Microsoft in the News Microsoft Canada and the British Columbia Cancer Foundation have partnered to take a radical approach to cancer research.  By taking advantage of Microsoft’s AI and Azure, BC cancer researchers hope to accelerate the pace of research into some very complex problems. The BC Cancer Foundation is applying a new approach called […]

TDSP Lifecycle – Deployment

Microsoft in the News Not that long ago, Microsoft deployed three business apps to supplement Microsoft 365 Premium.  They are:  Listings, Connections, and Invoicing.  In case you missed them, here is a brief rundown of what they do: Listings Microsoft Listings is a dashboard that allows you to manage your business information across Facebook, Google, […]

Algorithms Part 2 – Neural network, SVMs and Bayesian

To round out the algorithms this week we will look more deeply at Neural network, SVMs and Bayesian algorithms. Neural Network algorithms are used when the result you are looking for is a moving target and there are a large number of possible inputs, none of which have a strong individual correlation to the final result.  Programmers […]

Algorithms part one seeing the forest thru the trees

As you peruse your options in Azure ML, it is helpful to understand what it is you are looking at. For those of us who are not Data Scientists this world has a lot of new language and processes to learn. Understanding how and when to use the various types of ML algorithms is your […]

Types of Algorithms

I talked  recently about the process of choosing the right algorithm involving a lot of trial and error. Using the Algorithm Cheat Sheet provided by Microsoft is a great start, but, having a basic understanding of how the various algorithms work will certainly help guide you towards the one that is right for your situation. There […]

SQL Data Warehouse and Azure ML

Great news, on April 4th Microsoft announced support for Azure SQL Data Warehouse as a data source and a destination in Azure Machine Learning. It is exciting to now be able to use the Azure SQL Database connection options in the Reader and Writer modules to interact with the Azure SQL Data Warehouse. It is […]

Before You Start on Your Own Experiment

In my last post, I walked you through the process of running an experiment with Azure Machine Learning. Before you jump into your own experiment, you would do well to check out some examples first. Microsoft has provided many examples of experiments, and you may be able to find something similar to what you want […]

Getting Started with Azure Machine Learning

It is time to play! A good place to start is by downloading the Azure Machine Learning Studio Overview diagram. Download the diagram here: Microsoft Azure Machine Learning Studio Capabilities Overview (Keep this diagram handy as you navigate your way around the Learning Studio). As mentioned in a previous post, you can try Azure ML […]

Azure Machine Learning Studio (ML Studio)

To make it easy for you to work with Azure ML, Microsoft built the Azure Machine Learning Studio (ML Studio). This is a drag-and-drop environment where you go to build, test and run your predictive analytics. The data can be loaded in one of several ways. One way is to use the Reader module. The […]