23

Jan

Care and Feeding of Predictive Maintenance Solutions
Care and Feeding of Predictive Maintenance Solutions

This post is authored by John Ehrlinger, Data Scientist at Microsoft.

Microsoft has recently launched Azure Machine Learning services (AML) to public preview. The updated services include a Workbench application plus command-line tools to assist in developing and managing machine learning solutions through the entire data science life cycle. An Experimentation Service handles the execution of ML experiments and provides project management, Git integration, access control, roaming, and sharing of work. The Model Management Service allows data scientists and dev-ops teams to deploy predictive models into a wide variety of environments. Model versions and lineage are tracked from training runs to deployments while being stored, registered, and managed in the cloud.

Once AML Workbench is installed, the app connects to a Gallery of prebuilt real world data science scenario projects to help new users explore Azure ML, as well as give users a jump start on their specific data science scenarios.

The AML gallery currently contains two predictive maintenance example scenarios:

A PySpark implementation using a random forest of decision trees classifiers:
https://docs.microsoft.com/en-us/azure/machine-learning/preview/scenario-predictive-maintenance
A deep learning approach using an LSTM classifier:
https://docs.microsoft.com/en-us/azure/machine-learning/preview/scenario-deep-learning-for-predictive-maintenance

This post is written specifically to prepare users interested in using their own data to deploy customized predictive maintenance scenarios.

23

Jan

On-premises data gateway January update is now available
On-premises data gateway January update is now available

https://powerbi.microsoft.com/en-us/blog/on-premises-data-gateway-january-update-is-now-available/Source: https://powerbi.microsoft.com/en-us/blog/on-premises-data-gateway-january-update-is-now-available/           We are excited to announce that we have just released the January update for the On-premises data gateway. Here are some of the things that we would like to highlight with this month’s READ MORE

22

Jan

Custom Vision Service: Code-Free Automated Machine Learning for Image Classification

Re-posted from the Microsoft Azure blog.

Artificial Intelligence (AI) is a hugely disruptive force, one that is powering much of the digital transformation businesses are going through in recent times. At Microsoft, our mission is to bring AI to every developer and every organization on the planet, and to help businesses augment human ingenuity in unique and differentiated ways.

Developers and data scientists are at the heart of this transformation and the mission for the Microsoft AI platform is to offer the very best tools to make them successful in this journey. These include tools for automating machine learning through the pre-built AI capabilities we offer for vision, speech, language, knowledge and search in the form of the Microsoft Cognitive Services, which are enabling a rich variety of customer scenarios. As an example, when we announced the general availability of our conversational AI tools last month, we showcased innovative applications from leading edge customers such as Molson Coors, UPS and many others.

We continue to innovate on our AI platform at a rapid pace and wish to make AI easy by bringing capabilities such as transfer learning and automated machine learning to developers.

In this context, we are excited

22

Jan

SQL Server 2017 on Linux webcast series
SQL Server 2017 on Linux webcast series

The world’s leading database is now available on Linux by bringing Microsoft SQL Server to Linux, Microsoft continues to embrace open source solutions.

SQL Server 2017 brings the best features of the Microsoft relational database engine to the enterprise Linux ecosystem, including SQL Server Agent, Azure Active Directory (Azure AD) authentication, best-in-class high availability/ disaster recovery, and unparalleled data security.

Note that SQL Server on Linux is not a port or rewrite. This is the same world-class Microsoft relational database management system (RDBMS) now available on more operating systems (like Red Hat Enterprise Linux, SUSE Linux Enterprise Server, and Ubuntu) and more cloud and container platforms (like Docker).

Join us for one or all of a three-part webcast series now available on demand as we explore how SQL Server 2017 brings the industry-leading Microsoft relational database engine to the enterprise Linux ecosystem with our partners from Intel, Red Hat and HPE.

Session One:

SQL Server 2017 on Linux- #1 in price and performance—with massive scale
Learn how you can get record breaking performance with SQL Server on Linux. SQL Server consistently leads in the TPC-E OLTP workload, the TPC-H data warehousing workload, and real-world application performance benchmarks.

Presented by

19

Jan

Show off your skills with #AzureTrivia
Show off your skills with #AzureTrivia

When you were a kid, everything you encountered was novel and filled you with a sense of wonder. You were an explorer. An inventor. A scientist. A gamer. An astronaut.

Now, you’re solving problems with technology and the curious mind you’ve always had.

#AzureTrivia wants to celebrate the curiosity that keeps you so inspired. Join us, have some fun and show off your whip-smart Azure knowledge—bragging rights are on the line.

Every Monday @Azure will tweet out an Azure-related question. Want to test your Azure acumen and win* something cool? Just click on your selected answer, and if you tweet the correct answer no later than Thursday using the handy tweet we wrote for you (be sure to keep #AzureTrivia and the image), you’ll be entered to win a weekly prize (cool swag and other goodies). Pro tip: Be sure to come back every week for a brand-new question and another chance to win. 

If you love playing #AzureTrivia and want a competitive edge, check out these free Azure learning resources and get your win on!

FAQs

How do I enter?

It’s easy! Follow three simple steps by Thursday at 11:59PM Pacific Time:

Visit twitter.com/azure and follow @Azure.

19

Jan

Jan 23rd The Powerful Interactions between Excel and Power BI by Tristan Malherbe

https://powerbi.microsoft.com/en-us/blog/jan-18-the-powerful-interactions-between-excel-and-power-bi-by-tristan-malherbe/Source: https://powerbi.microsoft.com/en-us/blog/jan-18-the-powerful-interactions-between-excel-and-power-bi-by-tristan-malherbe/           See all the interactions between Excel and Power BI (Power BI in Excel, Excel connector, Power BI Publisher for Excel, Analyse in Excel, Export to Excel, push Data model from Excel to Power READ MORE

18

Jan

Webinar: Modernize your applications with cloud and on-premises data solutions from Microsoft

Customers today demand the latest innovations in every solution you deliver. How can you make sure your data infrastructure not only keeps up, but drives innovation?

Data is the core of modern applications. Two key trends that help organizations extract the most from their data are the adoption of cloud technologies and the ability to drive new customer experiences with artificial intelligence. Organizations that modernize and harness data, cloud, and AI outperform their competition and are becoming leaders in their field. The most digitally transformed enterprises earn an additional $100 million in operating income!

Join our speakers Claudia Backus, Prem Prakash, and Frederico Rezende for a webinar on how you can transform your applications and enable new customer experiences using the Microsoft data platform.

In this webinar, you’ll learn:

How to leverage the performance, security and flexibility of the entire Microsoft database portfolio from SQL Server 2017 and Azure SQL Database to open-source databases like Azure Database for MySQL and Azure Database for PostgreSQL. How to accelerate your move towards a cloud-based application with the new Azure Database Migration Service. How the Microsoft Data Accelerator program can help you modernize your apps across on-premise and cloud.

Register now for this

18

Jan

Deep Learning & Computer Vision in the Microsoft Azure Cloud
Deep Learning & Computer Vision in the Microsoft Azure Cloud

This is the first in a multi-part series by guest blogger Adrian Rosebrock. Adrian writes at PyImageSearch.com about computer vision and deep learning using Python, and he recently finished authoring a new book on deep learning for computer vision and image recognition.

Introduction

I had two goals when I set out to write my new book, Deep Learning for Computer Vision with Python. The first was to create a book/self-study program that was accessible to both novices and experienced researchers and practitioners — we start off with the fundamentals of neural networks and machine learning and by the end of the program you’re training state-of-the-art networks on the ImageNet dataset from scratch. My second goal was to provide a book that included:

Practical walkthroughs that present solutions to actual, real-world deep learning classification problems.
Hands-on tutorials (with accompanying code) that not only show you the algorithms behind deep learning for computer vision but their implementations as well.
A no-nonsense teaching style that cuts through all the cruft and helps you on your path to deep learning + computer vision mastery for visual recognition.

Along the way I quickly realized that a stumbling block for many readers is configuring their development environment — especially true for

18

Jan

Deep Learning & Computer Vision in the Microsoft Azure Cloud
Deep Learning & Computer Vision in the Microsoft Azure Cloud

This is the first in a multi-part series by guest blogger Adrian Rosebrock. Adrian writes at PyImageSearch.com about computer vision and deep learning using Python, and he recently finished authoring a new book on deep learning for computer vision and image recognition.

Introduction

I had two goals when I set out to write my new book, Deep Learning for Computer Vision with Python. The first was to create a book/self-study program that was accessible to both novices and experienced researchers and practitioners — we start off with the fundamentals of neural networks and machine learning and by the end of the program you’re training state-of-the-art networks on the ImageNet dataset from scratch. My second goal was to provide a book that included:

Practical walkthroughs that present solutions to actual, real-world deep learning classification problems.
Hands-on tutorials (with accompanying code) that not only show you the algorithms behind deep learning for computer vision but their implementations as well.
A no-nonsense teaching style that cuts through all the cruft and helps you on your path to deep learning + computer vision mastery for visual recognition.

Along the way I quickly realized that a stumbling block for many readers is configuring their development environment — especially true for

18

Jan

December 2017 Leaderboard of Database Systems contributors on MSDN

Congratulations to our December top 10 contributors! Alberto Morillo and Visakh Murukesan maintain their top positions.

This Leaderboard initiative was started in October 2016 to recognize the top Database Systems contributors on MSDN forums. The following continues to be the points hierarchy (in decreasing order of points):