AI April Content Dashboard
Looking to expand your AI knowledge this April? Great news- it’s AI April! Our team will be posting blog posts, videos and challenges around Azure Cognitive Services, Azure Machine Learning, Natural Language Processing, Quantum ML and more.
We’ll be sharing a new piece of content each day. Check back here April 1st- 30th for amazing new content to learn how Microsoft can empower you to do more you with AI/ML.
If you are new to Azure you can get started a free subscription using the link below.
Today’s Content — Evaluating Deep Learning Models in 10 Different Languages (With Examples)
ONNX is an open format built to represent machine learning models. ONNX defines a common set of operators — the building blocks of machine learning and deep learning models — and a common file format to enable AI developers to use models with a variety of frameworks, tools, runtimes, and compilers. The following post is a compilation of code samples showing how to evaluate Onnx Models in 10 different programming languages.
Content Calendar
April 29th — DeepPavlov: “Keras” for Natural Language Processing answers COVID Questions
In the field of image-related deep learning, Keras library plays an important role, radically simplifying such tasks as transfer learning or using pre-trained models. If you switch to the area of NLP, to perform relatively complex task such as question answering or intent classification, you would need to put several models at work together. In this post, I describe DeepPavlov library that democratizes NLP, and how to use it with Azure ML to train question answering network on COVID dataset.
April 28th — Quantum Machine Learning and Azure Quantum
Alex Bocharov, Principal Researcher at Microsoft Quantum Systems group and Chris Granade, Senior Research Software Development Engineer join Vadim Karpusenko to discuss the impact of Quantum Computing on the Machine Learning and Artificial Intelligence domains. Touching briefly on decade-old pioneering results in Quantum Machine Learning, the story switches to describe more recent technologies meant for near term generation of smaller “noisy” quantum computers. The second part of the interview showcases how you can get started using quantum machine learning with Q# and the QML library provided with the Microsoft Quantum Development Kit.
April 27th AI April NLP Math Teacher Challenge
For #AI April we’ve re-released the NLP Math Teacher Challenge. Check It Out! Build a model that can perform automatic problem solving, written in natural language on the provided Microsoft open dataset.
April 26th —Would you trust an AI to …? A list of questions to help you figure out the answer
An great overview of AI ethics by Amy Boyd
April 24th — 10 top tips for reproducible Machine Learning
The one where you get some advice to make your workflows more reproducible. The boom of Machine Learning and AI solutions is undeniable. We have “AI” enabled everything: from medical diagnosis optimization to HR and beer brewing processes.
April 23rd — Extracting Form Data to JSON, Excel & Pandas with Azure Form Recognizer
The Azure Form Recognizer is a Cognitive Service that uses machine learning technology to identify and extract text, key/value pairs and table data from form documents. It ingests text from forms and outputs structured data that includes the relationships in the original file.This post shows how to extract data from table images for pandas and Excel using the Azure Form Recognizer Service in Python.
April 22nd — Protecting Personal Identifiable Information with Azure AI
Today’s post outlines both first party and open source techniques for detecting PII with Azure.
April 21st — Create your own vision alerting system with IoT Edge, Azure Custom Vision and a Jetson Nano
In Today’s article Henk Boelman will guide you through the steps needed to create your own object alerting system running on an edge device. For this we will use an NVidia Jetson Nano, the Azure Custom Vision service and Azure IoT Edge.
The goal is to process the camera frames locally on the Jetson Nano and only send a message to the cloud when the detected object hits a certain confidence threshold.
April 20th — The Cognitive Services + Xamarin Combo Challenge! | Xamarin Blog
Summer is almost here! (Well, for those of us in the Northern Hemisphere anyway.) And while summer usually means it is time to travel and see the world, most of us are stuck inside right now. However, not to worry — our good friend Gerald Versluis has a way to, not only help pass the time, it will also help explore you the world once you can go outside. Additionally, you can get some cool Xamarin swag along the way. That’s right, it is challenge time! This time the Cognitive Services + Xamarin Combo Challenge!
April 17th — ONNX: No, it’s not a Pokemon! Deploy your ONNX model with C# and Azure Functions
Ok you got a ML model working in Jupyter notebook, now what? Lets deploy it! There are many ways to operationalize your model. In this tutorial we are going to be using the ONNX model format and runtime. ONNX gives you the ability to use the same model and application code across different platforms. This means I can create this model in Python with SciKit Learn and use the resulting model in C#! Say whaaat? Yes, that is right. Save it to ONNX format then run it and do the inferencing in C# with the onnxruntime!
April 16th — 10 Azure ML Code Examples Every Cloud AI Developer Should Know
The Azure ML Python SDK enables Data scientists, AI engineers,and MLOps developers to be productive in the cloud. This post highlights 10 examples every cloud AI developer should know, to be successful with Azure ML
April 15th — Making an Interactive Cognitive Portrait Exhibit using some Creativity, .NET, Azure Functions and Cognitive Services Magic
This January, Moscow ElectroMuseum made an open call for Open Museum 2020 Exhibition. In this post, Dmitry Soshnikov describes his submission, and how it was transformed due to quarantine and museum closing.
April 13th — Can AI be Creative? Let’s Find Out!
Generative Adversarial Network can produce a lot of original paintings much much faster than human painter. But does it make AI creative? Let’s discuss the nature of creativity, and try to challenge Artificial Intelligence on this front.
April 10th — 3 Tips for Debugging Cloud Scale Machine Learning Workloads
Let’s say you built an amazingly wonderful hand-crafted artisanal convolutional neural network that works beautifully on your hard-drive based dataset. You are now ready to take this masterpiece to the cloud to work on a much larger dataset on beefier machines — you are not looking forward to it.
- “How do I ship this patchwork conda (or venv) where I’ve installed everything the training/inference code needed AS WELL AS everything else I thought I needed along the way?”
- “I don’t want to waste cloud compute money on things I’m not sure will work on the first try!!”
- Basically, “I have already done the work and I’m not interested in the yak shaving portion of the job!”
No need to fear, dear reader, this article is designed to help you move your glorious work to the cloud (and beyond) by leveraging your local environment as if it were the cloud itself.
April 9th — Making Use of Unstructured Data with Form Recognizer
Every business has their “junk” drawer (or the “share” as Bill/Karen likes to call it). Often hidden in this data wasteland are nuggets of informational gold that could revolutionize the way you do business (we hope). Turns out that the most important information is usually hidden in paper forms (by paper I mean digital paper like an image or pdf file). Microsoft recently released a new service (still in preview) called Form Recognizer designed to make short work of the structured data hidden in these gems. This post shall endeavor to take you through the simple process here!
April 8th — Creating Generative Art using GANs on Azure ML
Deep Learning can look like Magic! I get the most magical feeling when watching neural network doing something creative, for example learning to produce paintings like an artist. Technology behind this is called Generative Adversarial Networks, and in this post we will look at how to train such a network on Azure Machine Learning Service.
April 7th — Attendance Estimation with C-3-Framework and Azure ML
This post provides an E2E Jupyter notebook for training crowd counting models with C-3-Framework and AzureML SDK for Python.
April 6th — Computer Vision Challenges: Why my neural network called me a punching bag…
We can visualize what neural network is “looking” at when making a prediction. Some of them are ridiculous and funny. Do you want to know how it’s done? Do you want to share your findings? Join our #CVchallenge during #AIApril.
April 5th — Image Classification with TensorFlow Lite & Azure Services | Xamarin Blog
Check out how to do cross platform mobile image classification Custom Vision and Xamarin.
April 4th — 1-Click Deployment of Cognitive Services with ARM Templates
Learn how to do 1-Click Deployment of Azure Cognitive Services with ARM templates with Maxime Rouiller.
April 3rd — Making Sense of the Senses- Our Top 5 Microsoft Azure Cognitive Services Combos!
If you’re trying to make sense of Azure Cognitive Services and determine which of the 5 senses you can use to make remote presentations more exciting with Azure- this post is for you!
In the post, Cloud Advocates Chloe Condon & David Smith will share their favorite combos of cognitive services to spice up your remote presentations and streams.
April 2nd — How YOU Can Use Computer Vision to Avoid Touching Your Face!
The first post for Azure April is an amazing walkthrough that demonstrates how to build a custom vision model to build an app that yells at you if you touch your face, as a way of helping people prevent the spread of COVID-19.
April 1st — This Post, let your friends know about the AIApril!
Additional Amazing Azure AI Resources:
About the Author
Aaron (Ari) Bornstein is an AI researcher with a passion for history, engaging with new technologies and computational medicine. As an Open Source Engineer at Microsoft’s Cloud Developer Advocacy team, he collaborates with Israeli Hi-Tech Community, to solve real world problems with game changing technologies that are then documented, open sourced, and shared with the rest of the world.
