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We moved our TFS to the cloud April 2017 | View Online
We moved our TFS to the cloud
 

We moved our TFS to the cloud

Previously at SSW, we had TFS on-premises (at tfs.ssw.com.au) and TFS in the cloud (at ssw.visualstudio.com) and I let the devs choose where they wanted to place new projects. Initially I was surprised to notice that most projects went in the cloud. Eventually I noticed they *always* chose the cloud. So I'm happy to announce we have migrated everything.

Our TFS migration went well and if we did today, it would go even smoother. We have a good relationship with the Visual Studio and TFS teams, and for our migration we had some bumpy bits. Rogan Ferguson from the TFS Database Import Service Team helped us plenty and we gave some feedback and it was impressive to see the fixes done so quickly

Keep reading to find out how we did it, and what the benefits are.

- Adam Cogan, SSW Got a comment for Adam?
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See the SSW guys run their 2 day Angular Course at the SSW Chapel in Sydney. SSW runs multiple Angular courses all over Australia. Check out The Angular Super Powers Tour to find out more.

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April User Group - Sydney

 

Sydney .NET User Group: An Introduction to Data Science on Azure - Nick Wienholt

Microsoft Azure provides a rich canvas for data science research and execution. Two of the key components of the data science toolkit are Azure Notebooks and the Azure Machine Learning service. In this presentation, Nick will introduce the core concepts of data science and show how a data set can be imported, analysed and used as the basis for a predictive model using these two Azure components.

Azure Notebooks are an implementation of the Jupyter notebook technology (formerly IPython notebooks) that allows code and markdown to be created in a browser document for interactive execution. Jupyter notebooks attach to a back-end kernel for code execution, and can support much greater computational loads and richer functionality than client-side Javascript technology. By supporting the mixing of documentation and live code, Azure Notebooks are an ideal technology for conducting and sharing data exploration exercises, and solve a number of issues that occur when analysis and the documentation are handled separately. Azure Notebooks currently support Python 2, Python 3, R and F#.

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Nick Wienholt

About the presenter

Nick is a solution architect at SSW with a 20 year career in software engineering primarily focussed on large scale software projects in the financial industry. He has written a number of books and dozens of article on .NET, and has been awarded the MVP award by Microsoft for the .NET platform, C# and C++. He has a keen interest in data science, and sees the possibility of great productivity gains by achieving a deeper melding of the traditional software development world with emerging data science disciplines.

 
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Sydney .NET User Group and NerdDinner proudly sponsored by:
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Canberra note: Due to the Easter Monday public holiday for on Monday April 17, this user group will be running 1 day later on Tuesday April 18.

 

April User Group - Canberra

 

Canberra .NET User Group: An Introduction to Data Science on Azure - Nick Wienholt

Microsoft Azure provides a rich canvas for data science research and execution. Two of the key components of the data science toolkit are Azure Notebooks and the Azure Machine Learning service. In this presentation, Nick will introduce the core concepts of data science and show how a data set can be imported, analysed and used as the basis for a predictive model using these two Azure components.

Azure Notebooks are an implementation of the Jupyter notebook technology (formerly IPython notebooks) that allows code and markdown to be created in a browser document for interactive execution. Jupyter notebooks attach to a back-end kernel for code execution, and can support much greater computational loads and richer functionality than client-side Javascript technology. By supporting the mixing of documentation and live code, Azure Notebooks are an ideal technology for conducting and sharing data exploration exercises, and solve a number of issues that occur when analysis and the documentation are handled separately. Azure Notebooks currently support Python 2, Python 3, R and F#.

Azure Machine Learning is part of the Cortana Intelligence suite, and allows for the interactive creation of experiments supporting a wide range of machine learning algorithms. The machine learning experiments can be evaluated for effectiveness, and easily turned into web service endpoints for machine learning prediction based on live data.

This presentation assumes no prior experience with machine learning, and will introduce the topics for a traditional software developers perspective.


Nick Wienholt

About the presenter

Nick is a solution architect at SSW with a 20 year career in software engineering primarily focussed on large scale software projects in the financial industry. He has written a number of books and dozens of article on .NET, and has been awarded the MVP award by Microsoft for the .NET platform, C# and C++. He has a keen interest in data science, and sees the possibility of great productivity gains by achieving a deeper melding of the traditional software development world with emerging data science disciplines.

 
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18
Tue
Microsoft Canberra Branch
Level 4, 6 National Circuit
Canberra
fb linkedin meetup
 
 
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