This month, The Data Incubator is hosting another free webinar on data science. This time it features an interview with Jake Porway, founder of DataKind. Jake and DataKind are doing amazing things, so I hope you can check out the webinar.
Below are the webinar details:
Data Science in 30 Minutes: Using Data Science in the Service of Humanity
Abstract: With his non-profit, DataKind, Jake Porway connects data scientists with social causes. Picture Doctors Without Borders for data nerds—with machine learning and AI engineers parachuting in to help the UN with humanitarian tasks, like tracking virus outbreaks using mobile data. “Data is like a bucket of crude oil,” Porway says. “Potentially great, but only if someone knows how to refine it (data scientists) and someone else has vehicles that will run on it (the social sector).” In this talk, Porway discusses the strategies of DataKind, its projects and the future of big data to service humanity.
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.
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
As of August 2018, full support is provided for C#, Javascript, and F#. Experimental support is provided for Batch, PowerShell, Python, and TypeScript. Python can be used to create an HTTP endpoint. This would allow someone to quickly create an endpoint for running machine learning models via scikit-learn or another python module. Unfortunately, R is not yet available, but Microsoft has a lot invested in R, so I am expecting this eventually.
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).
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]
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]
