Screen recording at youtu.be/cpCeaR9KTF8
MobileNet is a light-weight machine learning model for performing image classification.
In this Machine Learning for Kids project, students can try MobileNet for themselves using the familiar educational low-code programming language Scratch.
IBM Event Automation helps companies to accelerate their event-driven projects wherever businesses are on their journey. It provides multiple components (Event Streams, Event Endpoint Management, and Event Processing) which together lay the foundation of an event-driven architecture that can unlock the value of the streams of events that businesses have.
A key goal of Event Automation is to be composable. The three components can be used together, or they can each be used to extend and enhance an existing event-driven deployment.
Today, I demonstrated some of the Event Automation components working with Azure Event Hubs for Apache Kafka. As Event Hubs provides a Kafka interface to Azure’s data streaming service, it obviously can be used with Event Automation. But it can be helpful to inspire people by showing it for real, so even demos of obvious things can be valuable.
For example, Event Endpoint Management can enhance the value of topics in Event Hubs by offering management and governance, and by enabling governed reuse of those topics. Event Processing makes it easy to get insights from the events on Event Hubs topics, by providing an intuitive low-code authoring canvas to process them.
If I was going to be running this for a while and wanted to optimise for my applications in Azure, I would likely have set this up like this, with the Event Gateways deployed close to the Azure Kafka endpoints.
Machine Learning for Kids is intended to be an open creative sandbox to let students invent their own AI-powered projects. But in order to enable that, I create more prescriptive project worksheets to inspire and show what is possible.
I’ve just written another worksheet based around regression models – a model type that I added support for in February.
This project is based on shooting basketballs.
Students are free to devise their own projects in Machine Learning for Kids, but I also write project worksheets to help inspire students and teachers.
This evening, I’ve written a new worksheet based around regression models. (I wrote about adding support for regression models to the site a couple months ago).
The premise for this project is sort of Space Invaders. Except with only a single Space Invader. And it’s a cute little bug.
The aim of the game is to shoot at the bug.
I added support for “local projects” (storing projects on your own computer) to Machine Learning for Kids this week. In this post, I want to give a little background.
Extensions in Scratch let you add additional blocks to the palette. I’ve written about how to create extensions before, but in this post I want to share my latest extension which adds MQTT support.
I don’t have a particular Scratch project in mind for this yet, but publishing and subscribing to an MQTT broker from a Scratch project would allow multiple web browsers each running Scratch to communicate with each other. I’m sure there are some fun things this could be used for.
This is a talk I gave at Kafka Summit last month. It was an introduction to the Java APIs for Kafka Connect and Kafka Streams, using data from Xbox to bring the examples to life.
Confluent require personal details to watch recordings from Kafka Summit – sorry
One of the conference presentations I gave last year was a talk at Heapcon, sharing some stories of AI/ML lessons I’ve run in schools. The focus of the talk was how I’ve seen children understand and react to machine learning technologies.
I’ve since expanded the ideas in this talk into a mini-book at MachineLearningForKids.co.uk/stories but here is a recording of where some of these stories started.