Picture Perfect: Image Analysis with OpenCV for .NET Devs

OpenCV (Open Source Computer Vision Library) is an open-source computer vision and machine learning software library. OpenCVSharp is a cross-platform wrapper of OpenCV for .NET. Attend this session to learn how to process and analyze the content of images, including recognizing objects, tracking movement, converting images, applying machine learning methods, and identifying common elements in images.

Aloha, World! Introduction to ML.NET and MAUI

MAUI (Multi-platform App UI) is a UI framework for making Windows, iOS, Android, and macOS applications with one project and one codebase. Attend this session and learn how to build and train a custom machine-learning model using ML.NET Model Builder then we will demonstrate how to integrate it into MAUI app.

Predictive Maintenance using ML.NET Model Builder

Predicting the future is not easy! Forecasting peak operating conditions and avoiding unexpected equipment breakdown is possible, that's the goal of Predictive Maintenance. Attend this session and learn how to train a machine learning model in Visual Studio with ML.NET Model Builder, and build an app that uses the model. Fair warning - I cannot predict how live demos would go. I will do my best.

Making neural networks run in browser with ONNX

The world of machine learning frameworks is complex. What if we can use the lightest framework for inferencing on edge devices? That’s the idea behind ONNX format. Attend this session and find out how to train models using the framework of your choice, save or convert models into ONNX, and deploy to cloud and edge using a high-performance runtime in javascript.

Leverage the Power of Machine Learning with ONNX

Have you ever wanted to make your apps smarter? This session will cover what every ML/AI developer should know about Open Neural Network Exchange (ONNX) . Why it’s important and how it can reduce friction in incorporating machine learning models to your apps. We will show how to train models using the framework of your choice, save or convert models into ONNX, and deploy to cloud and edge using a high-performance runtime in javascript.

Predicting the future (of equipment) using ML.NET

Predicting the future is not easy! Forecasting peak operating conditions and avoiding unexpected equipment breakdown is possible, that’s the goal of Predictive Maintenance. Attend this session and learn how to train a machine learning model in Visual Studio with ML.NET Model Builder, and build an app that uses the model. Fair warning - I cannot predict how live demos would go. I will do my best.

Mixed Reality for JavaScript developers

Mixed Reality features are available on the web through the use of WebXR. Experience virtual reality (VR) and augmented reality (AR) content in a compatible WebXR-enabled browser. Attend this session and leverage the power of JavaScript and web skills to create more engaging Mixed Reality experiences. We will look at popular open-source AR/VR JavaScript libraries available to get started.

From Scribbles to Insights: Extracting Data from Paper Forms in Azure

Getting feedback from the presentation is good; Getting hand-written paper surveys, not so good. Collecting and compiling them is a chore. Let's turn this paper trail into usable data and shift our focus to acting on information rather than compiling it. Attend this session to learn more about the Azure Forms Recognizer; I will be asking attendees to fill out a feedback paper form, and submit it. Then we'll learn how to extract text, key-value pairs, tables, and structures from the document.

Forms are part of any business, sometimes they are digital forms, and sometimes they are paper forms. My goal here is to demonstrate a good use case for collecting data from paper forms generated by the audience. I will ask the audience to give me feedback for the first 20 minutes of my talk, as part of the demo, the audience would submit the paper form and will use Azure Forms recognizer to understand text written by the audience.

Managing IoT Devices in Azure; the simpler way

Collecting telemetry data from devices is a common requirement today for any IoT solution. In this session, we will learn about Azure IoT Central and how it reduces the burden and cost of developing, managing, and maintaining IoT applications. Journey with me as we will walk through different features of IoT Central: connect devices, monitor, configure rules, and integrate with other services. Learn how to customize IoT central to fit the needs.

Serverless at the edge in Azure Percept

While Azure Percept brings AI at the edge, Azure Functions allow deploy code that implements business logic directly to IoT Edge devices. Attend this presentation to learn more about creating and deploying an Azure Function that filters data from an Azure Percept Device.

AI to the edge with Azure Percept

AI-enabled IoT creates intelligent machines that simulate smart behavior and support in decision-making with little or no human interference. Attend this session and use Azure Percept to collect data, learn about machine learning to train custom object detection model, deploy model and manage edge device.

Intro to Azure Percept: Teaching devices to 'see, hear, speak no evil'

Transfer learning is a machine learning technique where a model trained on one task is re-purposed on a second related task. Attend this session to learn about using transfer learning to train custom object detection model, use Azure Percept to collect data, deploy model and manage edge device.

Men from Mars, Women from Venus: both can code .NET in Jupyter

Jupyter Notebook is an open-source web application that allows you to create and share documents that contain live code, equations, visualizations and narrative text. Attend this session and learn how you can write .NET code with Jupyter Notebooks running in Raspberry Pi; read sensor data, build dashboard and control an IoT device all from the browser.

Making neural networks portable with ONNX

The world of machine learning frameworks is complex. What if we can use the lightest framework for inferencing on edge devices? That’s the idea behind ONNX format. Attend this session and find out how to train models using the framework of your choice, save or convert models into ONNX, and deploy to cloud and edge using a high-performance runtime in python, C# or javascript.

Developing Spidey Senses : Anomaly Detection for javascript apps

Anomaly detection is the process of identifying unexpected items or events in data sets. It’s about detecting the deviation from expected pattern of a dataset. It’s like having “spidey senses” for your apps that can detect when there’s danger or something is not right. Attend this session and learn about using anomaly detection in javascript and Cognitive Services API, become a superhero and save the day.

Build Intelligent applications with ML.NET and Windows Machine Learning

Need to integrate trained machine learning models into Windows apps? In this session, we will look into how Windows Machine Learning can transform applications with the power of artificial intelligence and run it on the devices by taking full advantage of hardware acceleration. We will walk thru and learn how to train a model with ML.NET Model Builder and inference with Windows Machine Learning.

Processing AI data streams at the Edge

While Azure Percept brings AI to the edge, various docker containers can process telemetry streams and implement business logic directly in edge devices. Attend this presentation to learn more about creating and deploying custom docker containers and Azure Stream Analytics on IoT Edge that filters data in an Azure Percept Device.

Machine Learning in small, low-powered devices

Machine learning (ML) is a way of writing computer programs. The difference is that the rules of ML programs are not determined by a developer but by training the machine. Attend this session and we will
collect a substantial set of training data from a device, feed it into a special kind of algorithm that will discover the rules then convert it to a TinyML model. We will deploy the TinyML model to a small, low-powered embedded device, test it and send output to Azure.

embedded machine learning models on edge devices

Exploring the land of IoT on Azure

IoT is not just about "things". What happens after data is collected from smarthomes, factories, electrical grids, buildings, security systems, and other things? The truth is IoT is more than "Internet" than "Things". Attend this presentation and we'll look at high-level architecture of an IoT deployment and how it's implemented in Azure land.

Oh what fun! connecting to devices with your browser

webUSB, webMIDI, webBluetooth, oh my web! In this session, we will explore webUSB, webMIDI, and webBluetooth API and how it safely exposes device services to the web using JavaScript. This session is designed for web developers who want to innovate and take their web apps to the next level.

From Pixels to Wizardry: Unleashing Visual Spells with OpenCV for .NET Magicians

Prepare to be spellbound as we transport you into the realm of image analysis! Join our enchanting session where the magic of OpenCV and OpenCVSharp combine, empowering .NET developers to weave wonders with images. Delve into the captivating art of deciphering images, where objects come to life, movement follows your command, and pixels bow to your will. From transforming images with sorcery to harnessing the power of machine learning incantations, we'll reveal the secrets to unveiling extraordinary elements hidden within ordinary visuals. Don't miss this mesmerizing presentation that will leave you bewitched by the endless possibilities of image sorcery!