Posts Tagged ‘mlforkids-tech’

How ML for Kids handles numbers models now

Thursday, April 4th, 2024

I’m on vacation for the Easter holidays this week. Apparently I don’t know how vacations work, so I’ve spent a lot of the last six days working on a major rewrite of a big chunk of Machine Learning for Kids. In this post, I want to describe what I’ve been doing and why.


Explaining regression in Scratch

Thursday, February 15th, 2024

In this post, I want to share a preview of a new feature I’m adding to Machine Learning for Kids, to ask for feedback and ideas for projects that it could be used to make.

I’ll start by contrasting this new feature with what I’ve done with Machine Learning for Kids before, then I’ll share screenshots of the new feature, and finally I’ve got a ten-minute video showing the sort of school lesson that I think it could be used for.


“Local projects” in Machine Learning for Kids

Friday, January 19th, 2024

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.


Machine Learning for Kids with EduBlocks

Saturday, July 8th, 2023

Students can now create Machine Learning for Kids projects using EduBlocks – letting them create machine learning Python projects in the browser by dragging and dropping blocks on a canvas.

This is all thanks to a fantastic new contribution from Joshua Lowe.

Here’s a quick run-through to show what this makes possible.


What children can learn about artificial intelligence

Sunday, May 21st, 2023

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 but here is a recording of where some of these stories started.

Spotify extension for Scratch

Saturday, December 17th, 2022

In this post, I want to share a new Scratch extension that I made this week, explain what it does, and suggest a few ideas for the sorts of ways that it could be used.


The extension makes some of the data from the Spotify Audio Features API available as blocks in Scratch.

It means you can get numeric values representing different characteristics of songs, directly into a Scratch project.


Geo-steering with IBM Code Engine and Cloud Internet Services

Saturday, September 3rd, 2022

In this post, I want to share a small tip from how I run Machine Learning for Kids: how I run instances of the site in different regions, and use geo-steering so that users are directed to the instance of the site nearest to them.


Using pitch estimation to play with music in Scratch

Tuesday, October 5th, 2021

I’ve added a pitch extraction machine learning model to Machine Learning for Kids today. In this post, I want to describe the model a little, and suggest a few ways that students could use it.


I started adding pretrained machine learning models to Machine Learning for Kids last year. Although my main focus is still allowing students to create their own machine learning models and make things with them, there are some fun projects that can be made using models that are too complex for students to train by themselves.

imagenet (that I added last Christmas), and the question-answering model (that I added in April) are both good examples of that!

I hope this one will be similarly welcomed!


The new model is a pitch estimation model. Given some audio as input, you can use it to recognize the dominant pitch in sung audio (even if there is background music and noise).