Using the Data Science VM within your classes

The Microsoft Data Science Virtual Machine or Deep Learning Virtual Machine are customized VM image on Microsoft’s Azure cloud built specifically for doing data science. It has many popular data science and other tools pre-installed and pre-configured to jump-start building intelligent applications for advanced analytics. It is available on Windows Server and Linux. We offer…

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Kusto Query Language with Azure Notebooks and Azure Data Explorer

Getting Started with KQL Microsoft Azure notebooks http://notebooks.azure.com now supports KQL, which enables notebooks to query big data stores such as Azure Log Analytics and Application Insights Analytics. You can get started using the KQL Sample notebooks in GitHub. This becomes even more interesting as Azure Data Explorer and its documentation is an excellent place…

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Microsoft Azure Notebooks and Additional Compute Capacity via connecting to Data Science VMs

If you sign into  Azure Notebooks http://notebooks.azure.com with an account associated with an Azure Subscription you will enjoy easier and deeper integration with your Azure resources including access to increased resource capacity. Azure Notebooks has offered FREE CPU compute, but users who have or sign up for with an Azure subscriptions can create Linux Data…

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Source Control for Data Science – using Azure DevOps / VSTS with Jupyter Notebooks

So many of you will know about https://mybinder.org/ Binder is a awesome tool that allows you turn a Git repo into a collection of interactive Jupyter notebooks and it allows you to, open those notebooks in an executable environment, making your code immediately reproducible by anyone, anywhere. Jupyter Notebooks in the cloud Another great interactive…

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Data Science in Visual Studio Code using Neuron, a new VS Code extension

Guest post by Lorenzo Silvestri, Electronic and Information Engineering Student at Imperial College London. Introduction In this post, I’ll give a short explanation of neuron, a Visual Studio Code extension that aims to be a one-stop-shop for data scientists. It’s an extension I developed as part of a team of students at Imperial College London,…

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Introduction to Data Science using F# and Azure Notebooks

Guest post by Nathan Lucaussy, Microsoft Student Partner at Oxford University. Introduction to Data Science using F# and Azure Notebooks – Part 1: Functional Programming Basics via Plotting and Genetic Algorithms Hello! I hope you’ll enjoy the following blog post – it details the particular kind of algorithm that got me so excited about studying…

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Visualising climate change using Jupyter Notebooks.

A beginners guide to using Jupyter Notebooks on the Microsoft Azure Notebooks services to visualise data  By T.T. Ouzounellis Kavlakonis Microsoft Student Partner at University of Cambridge  About Me: Hello planet Earth! Welcome to my first blog post. My name is Theo and I am a first year Engineering student at Trinity College, University of…

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Innovative assessment by deploying Ok.py and Microsoft Azure at Imperial College

Guest post by Victoria Murphy Imperial College London A new computational course in the Department of Earth Science & Engineering will benefit from innovative software deployed at Imperial College London. Students of the Applied Computational Science and Engineering MSc programme will develop software to solve real-world science and engineering problems, from modelling asteroid impacts to…

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Azure AI Gallery enables developers and data scientists to share their analytics solutions.

Azure AI Gallery is a community-driven site for discovering and sharing solutions. Learn how to contribute. The Gallery has a variety of resources that you can use to develop your own analytics solutions. Students can try Azure Machine Learning for free. No credit card or Azure subscription is required. http://aka.ms/azure4students What can I find in…

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Coding for biology using Jupyter Notebooks

Guest post by Dr Benjamin Hall  University of Cambridge Part of the new world of biology is understanding how to best use computers to do research. Whilst the field of computational biology isn’t new, novel ideas constantly in computer science and mathematics opening up new ways of working and addressing problems. Adopting these techniques can…

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