Month: May 2015

Register for this event in the time zone that suits you best:
June 2-3, 9am–1pm PDT (The Americas)
June 3-4, 9am–1pm CEST (Europe)
Do IT security concerns keep you up at night? You’re not alone! Many IT Pros want to extend their organization’s infrastructure but need reassurance about security. Whether you are researching a hybrid or a public cloud model with Microsoft Azure, the question remains the same: Does the solution meet your own personal and your organization’s bar for security, including industry standards, attestations, and ISO certifications?

In this two-part, demo-filled course, explore these and other hot topics, as a team of security experts and Azure engineers takes you beyond the basic certifications and explores what’s possible inside Azure. See how to design and use various technologies to ensure that you have the security and architecture you need to successfully launch your projects in the cloud. Dive into datacenter operations, virtual machine (VM) configuration, network architecture, and storage infrastructure. Get the information and the confidence you need, from the pros who know, as they demystify security in the cloud.

Post from Microsoft I thought would be of interest to you all

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This report is more that just Microsoft issues, it is a great read for any security Professional

Latest Microsoft Security Intelligence Report Now Available

Here are a few blogs based on the new data as well:

Mass vulnerabilities in Android applications spike industry vulnerability disclosures in 4th Quarter 2014

The life and times of an exploit

 Microsoft announces Free PC virus removal

No matter where you bought your PC, bring it into your local store for free virus and malware removal.

Learn more about Answer Desk Click Here

Azure Machine Learning  is a service that a developer can use to build predictive analytics models (using training datasets from a variety of data sources) and then easily deploy those models for consumption as cloud web services.

Microsoft Azure Machine Learning (ML) is a service that a developer can use to build predictive analytics models (using training datasets from a variety of data sources) and then easily deploy those models for consumption as cloud web services. Azure ML Studio provides rich functionality to support many end-to-end workflow scenarios for constructing predictive models, from easy access to common data sources, rich data exploration and visualization tools, application of popular ML algorithms, and powerful model evaluation, experimentation, and web publication tooling.

This ebook will present an overview of modern data science theory and principles, the associated workflow, and then cover some of the more common machine learning algorithms in use today. We will build a variety of predictive analytics models using real world data, evaluate several different machine learning algorithms and modeling strategies, and then deploy the finished models as machine learning web service on Azure within a matter of minutes. The book will also expand on a working Azure Machine Learning predictive model example to explore the types of client and server applications you can create to consume Azure Machine Learning web services.

The scenarios and end-to-end examples in this book are intended to provide sufficient information for you to quickly begin leveraging the capabilities of Azure ML Studio and then easily extend the sample scenarios to create your own powerful predictive analytic experiments. The book wraps up by providing details on how to apply “continuous learning” techniques to programmatically “retrain” Azure ML predictive models without any human intervention.

You can get the e-book here