Azure Data Week is a virtual conference for all things Microsoft Azure and data science. It takes place October 8-12, 2018. It is not free, but the cost is low and you do not have to travel.
The latest articles from Microsoft regarding cloud data science products and updates.
- Build Intelligent Web App with Machine Learning Service – In an earlier article: How to operationalize TensorFlow models in Microsoft Machine Learning Server, we showed how you can deploy a TensorFlow image classification model pre-trained using ImageNet as service in Machine Learning Server, and download a …[Read More]
- Measuring Model Goodness – Part 1 – Data and AI are transforming businesses worldwide from finance … actionable insights. This is where data science and machine learning come in. This entire process has been documented as the Team Data Science Process (TDSP) at Microsoft, captured in …[Read More]
- Driving industry transformation with Azure – Getting started – Edition 1 – Banking customers want more from their services … using AI and machine learning to detect patient risk and identify disease faster while maintaining privacy and protecting against fraud. IoT in manufacturing isn’t just about collecting data.[Read More]
- Speech Services August 2018 update – We are pleased to announce the release of another update to the Cognitive Services Speech SDK (version 0.6.0 … dev kits to significantly improve the audio quality of the audio data collected via the dev kits’ microphones, for high speech recognition …[Read More]
- Introducing yet another approach for iot compiler toolchains – iotz – iotz is an extension based containerized wrapper for other IoT compiler toolchains. There are many toolchains with specific needs and way of using. We developed this experimental tool to make compiling things easier. – cross compiling tools are mostly …[Read More]
- Design against crime & Microsoft Azure with Shiny – It is this app we will later learn how to deploy a shiny app onto Microsoft Azure services … including a review of data available via police.uk. We engaged with UCL to find a student from the Security and Crime Science course who could help us to …[Read More]
- Simplifying big data analytics architecture – manufacturing, retail education, nonprofit, government, healthcare, media, banking, telecommunication, insurance, and many more industries ranging in use cases from ETL to Data Warehousing, from Machine Learning to IoT, and more.[Read More]
Here are the latest articles from Microsoft regarding cloud data science products and updates.
- Advanced Analytics is coming into Azure Portal – We see Azure Monitor users are using both the Log Search page and the Analytics portal to accomplish their tasks. The Analytics portal offers advanced features, and we’re happy to announce it’s coming into Azure! …[Read More]
- Azure Custom Vision in action – Azure platform offers many ready-to-use cognitive services, allows you easily enrich your applications with innovative features. In this article we will see how to use the Custom Vision service. We will train a model to learn how to recognize some types of …[Read More]
- IoT in Action: Building secure, sophisticated solutions – Customers across industries are implementing increasingly sophisticated IoT solutions in countless scenarios to achieve their own unique objectives. From launching new products to creating new services to streamlining operations, our customers continue to …[Read More]
- Azure #HDInsight Interactive Query: simplifying big data analytics architecture – manufacturing, retail education, nonprofit, government, healthcare, media, banking, telecommunication, insurance, and many more industries ranging in use cases from ETL to Data Warehousing, from Machine Learning to IoT, and more.[Read More]
- Azure IoT Edge support for Raspbian 8.0/Debian 8.0 – In theory, Azure IoT Edge is working only for the version 9 of Debian. If you’re using a Raspberry Pi, you’ll most likely use a Raspbian version which is based on Debian. So same, you’ll have to be on the version 9 to be able to deploy Azure IoT Edge …[Read More]
- Service Fabric and Kubernetes comparison, part 1 – Distributed Systems Architecture – During the last decade, distributed services platforms are drawing more and more attention. These platforms are revolutionizing the way we think about systems architecture, bringing multiple theoretical computer science … Azure IoT Hub, Dynamics 365 …[Read More]
- The ‘What’ is known ? But ‘How’ is the gap ? – I must admit that, no conversation is complete these days without speaking about AI. While I reflect on many meetings I have had in the last 6-8 months, it is imperative that the next frontier of innovation revolves around ‘Data’, and ‘Independent Software …[Read More]
- The Microsoft AI Idea Challenge – Breakthrough Ideas Wanted! – data scientists, professionals and students, and preferably developed on the Microsoft AI platform and services. The challenge gives you a platform to freely share AI models and applications, so they are reusable and easily accessible. The ideas you submit …[Read More]
- Installing certificates into IoT devices – Lots of folks are moving to X.509 certificate-based authentication as they start to use the Azure IoT Hub Device Provisioning Service, which is great! But I’ve gotten lots of questions about what the best practices are, and how to go about doing it at scale.[Read More]
- Azure #HDInsight Apache Phoenix now supports Zeppelin – manufacturing, retail education, nonprofit, government, healthcare, media, banking, telecommunication, insurance, and many more industries ranging in use cases from ETL to Data Warehousing, from Machine Learning to IoT, and more.[Read More]
- Azure IoT Edge for VS Code 1.2.0 has been released – Now run IoT Edge modules with simulator – Now Azure IoT Edge for VS Code 1.2.0 has been released with a bunch of new features. What’s new in IoT Edge for VS Code 1.2.0 1.Now you and run IoT Edge solution with the built-in IoT Edge simulator without deploying to IoT Edge device. 2.You can watch …[Read More]
- Azure IoT Workbench now supports ESP32 devices – To learn more, visit tutorial for enabling OTA firmware with IoT DevKit. IoT devices generate continuous streams of data so the need for processing those data is now widely realized and reflected in IoT solutions. Azure Stream Analytics is Microsoft’s …[Read More]
- Data Platform & Analytics technical webinars & consultations – August, September & October – focused on Data and AI scenarios. You’ll learn how to sell and deploy solutions faster with technical guidance from a Microsoft expert. Participate in instructor-led webcasts that include interactive training and real-time Q&A capabilities. Register …[Read More]
- Building an Azure Event Grid app. Part 1: Event Grid Topic and a .NET Core custom app event publisher. – In order to have a sample “data feed” for an application I wanted to use Azure … The generic scenario is that of alarms (of whatever sort you’d imagine; car, house, IoT device) for which the events represent status updates. This is the first …[Read More]
Data Scientists do more than build fancy AI and machine learning models. They often times need to get involved with the data acquisition process. It is common for data to be pulled from other databases or even an API. Plus, the models need to be deployed. These tasks fall to the data scientist to solve (unless there is a data engineer willing to help). Recently, I have discovered Azure Functions to be an extremely useful tool for solving these types of tasks.
What are Azure Functions?
Simply stated, Azure Functions are pieces of code that run. More formally stated,
Azure Functions are serverless computing which allows code to run on-demand without the need to manage servers or hardware infrastructure.
This is exactly what a data scientist needs to solve the tasks mentioned above. I, for one, do not enjoy managing servers (hardware or virtual). I have done it before, but I find it time-consuming and tedious. It is just not my thing. Thus, I happily welcome the serverless capabilities of Azure Functions. I just focus on the code and get the task completed.
Because the code does not always need to be running, Azure Functions invoke the code based upon specified triggers. Once the trigger is activated, the code will begin to run. The following list provides some examples of the triggers available.
Triggers for Azure Functions:
- Timer – Set a timer to run the Azure Function as often as you like. Timing is specified with a cron expression.
- HTTP Rest call – Have some other code fire off an HTTP request to start the Azure Function.
- Blob storage – Run the Azure Function whenever a new file is added to a Blob storage account.
- Event Hubs – Event Hubs are often used for collecting real-time data, and this integration offers Azure Functions the ability to run when a real-time event occurs.
- Others – Cosmos DB, Service Bus, IoT Hub, GitHub are other events which can trigger an Azure Function.
What can Azure Functions Do?
Once you begin to understand the concept, you can quickly see some of the possibilities. Without having to configure servers or virtual machines, the following tasks become much simpler:
- Reading and writing data from a database
- Processing images
- Interacting with an HTTP endpoint
- Automating decisions in real-time
- Computing descriptive statistics
- Creating your own endpoint for other data scientists to call
- Automatically analyzing code after commits
Programming Languages for Azure Functions
Simplify Tasks for Data Science
Next time you have a data science task which requires a little coding, consider using an Azure Function to run the code. It will most likely save you some deployment and configuration time. Then you can quickly get back to optimizing those fancy AI models.
See the video below for a quick demonstration of how to create an Azure function via a web browser (no IDE needed).
Definition of AI:
Everything a computer can’t do yet.
Here are the latest articles from Microsoft regarding cloud data science products and updates.
- Basics of R and Python Execution in SQL Server – Ensure Machine Learning Services is already installed and enabled. After setup I will now show you the basics of executing R and Python code within a T-SQL statement. While I use Python in these samples, you can do everything with R as well. Open up SQL …[Read More]
- Emerging AI Patterns – Since that time, the Microsoft AI Solution for Customer Service, which is being used by Microsoft, HP, Macy’s, Australian Government Department of Human Services … Machine learning does a great job of detecting patterns in a vast amount of data …[Read More]
- Devs imagine, create, and code the future at Microsoft Build – Developers experienced HoloLens, programmed their own AI-powered drones, and explored cutting-edge IoT solutions amid myriad other … technologies like Azure Containers, Power BI, and Cognitive Services then discuss concepts with the Microsoft engineers …[Read More]
- Explore Build 2018 content with playlists – AI + Machine Learning AI + Machine Learning Create the next generation of applications using artificial intelligence capabilities for any developer and any scenario Containers Containers Develop and manage your containerized applications faster with …[Read More]
- Enterprise Deployment Tips for Azure Data Science Virtual Machine (DSVM) – The Data Science Virtual Machine (DSVM), a popular … with a host of preconfigured data and AI tools. It enables data scientists and AI developers to iterate on developing high quality predictive models and deep learning architectures and helps them …[Read More]
- Improving Medical Imaging Diagnostics Using Azure Machine Learning Package for Computer Vision – This post is by Ye Xing, Senior Data Scientist, Tao Wu … We recently witnessed this first-hand when we developed a deep learning model on the newly released Azure Machine Learning Package for Computer Vision (AML-CVP) and were able to improve upon …[Read More]
- Build Your Own Text Classification Model – In all three of these examples, machine learning models can help. The Text Classification solution on the Azure AI Gallery solves these multi-class text classification problems using SQL Server ML Services. Both R and Python solutions are included.[Read More]
- Episode 8: IT IQ Series – Predictive analytics: the “cheat-sheet” for more personalised teaching? – “When we feed these seemingly unrelated data sets into a platform like Azure Machine Learning, we can predict various potential problem sites with a reasonably high degree of accuracy. That, in turn, helps schools deploy their resources as well as work …[Read More]