Archive for the ‘misc’ Category

Machine learning workshop for school teachers

Friday, April 2nd, 2021

This week I ran a remote workshop for school teachers about machine learning and artificial intelligence. It was organised with University College London as part of a series of activities they are running to celebrate the CS Expo: 40+ years of UCL Computer Science.

It was quite a long session, as we wanted it to be a hands-on practical CPD (Continuing Professional Development) workshop rather than just me giving a short talk. In the 90-minute workshop, we made two separate AI projects, which was a chance to see and contrast a few different approaches.

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I wrote a book

Sunday, January 24th, 2021

It’s called “Machine Learning for Kids: A Project-Based Introduction to Artificial Intelligence”.

It’s a hands-on, application-based introduction to machine learning and artificial intelligence that guides young readers through creating compelling AI-powered games and applications using the Scratch programming language.

Since starting the Machine Learning for Kids site, I’ve written project worksheets to inspire students and teachers what can be built using the tool. By making them freely available as Creative Commons-licensed MS Word docs, they’ve been a jumping off point to help teachers and code-club leaders to create their own lessons and activities.

As I’ve written the worksheets with schools and code clubs in mind, that introduced constraints.

Each worksheet is self-contained – many schools will only have time in their timetable/curriculum for one, or maybe two, AI projects, so a lot of the projects retread some of the same basics. None of them build on, or even refer to, any of the other worksheets. They also need to be short activities, so that they can be completed within a school lesson.

Writing a book version of Machine Learning for Kids was a chance to do something for a different audience: this time aimed at a child at home with their parents.

This means I didn’t have the same constraints as the worksheets on the site. It’s still based on explaining machine learning in a hands-on way through making projects in Scratch. But there’s a flow between the projects in the book. They’re in an intentional order, and there is a continuation between them. Each project builds upon the projects that came before it.

Some of the projects take a bit longer as they don’t need to be done in one sitting. I have more time and space to explain the ideas and to give the real-world context for each project. As each project doesn’t need to work as an introduction, it means the later chapters can get into more advanced topics that none of the project worksheets on the site go near, like accuracy, recall, and confidence matrices.

It’s been a lot of work. A lot more than I expected. Over two years of work. And not just by me: I had no idea how many people would be involved in making the book into a real thing. I’ve not really worked with editors before, and it has been a fascinating experience. They made my rambling gibbering so so much better that I’m almost embarrassed that only my name is on the cover. There’s no way the finished thing would be nearly as good without their work.

There were a few points where I wondered if it’d ever actually see the light of day – but it’s finally available. (Well, the e-book is available now, but the printed version is still a couple of weeks away).

I hope people find it useful! I am proud of it. I’m particularly proud of the Foreword, which I didn’t even write. It was very generously written by Grady Booch, and it’s the perfect inspirational start to what I wanted the book to be.

It’s very strange to see something I’ve written in online bookshops. It’s in Amazon, Waterstones, and WHSmith. That feels a bit weird. I hope that at some point I’ll get to see a printed copy in a real bookshop, but I suspect that won’t be any time soon!

Looking back at Machine Learning for Kids in 2020

Saturday, January 2nd, 2021

A review of what I did on Machine Learning for Kids in 2020.

Happy New Year!

At this time of year, it’s traditional to get a bit reflective, so I thought I’d look over the work I did on ML for Kids in 2020.
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Introducing ‘Machine Learning for Kids’ to teachers

Thursday, December 17th, 2020

I gave a short talk about Machine Learning for Kids last week as part of an online conference run by Somerset eLIM. Here’s the recording.


youtu.be/8St1REZbE5w

I started with a couple of definitions, then demonstrated a variety of projects that I’ve seen primary school students make, and finally walked people through a hands-on demo so they could try it out for themselves.

#SwitchGameADay

Saturday, May 23rd, 2020

For a while now, I’ve been playing a different Nintendo Switch game every day, sharing a video clip on Twitter.

In this post I’ll collect together all of the clips, and the answers to the questions I’ve been asked along the way.


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The Artificial Intelligence Grand Challenge

Monday, November 4th, 2019

The first of the Grand Challenges identified in the Government’s Industrial Strategy is about Artificial Intelligence. One of the things that these challenges highlight is the UK’s need for skills in these key areas.

To that end, STEM Learning and the Department for Business, Energy and Industrial Strategy have created the “Grand Challenges – Our Futures” programme to improve young people’s knowledge of the STEM skills identified in the Government’s Industrial Strategy Grand Challenges.

Last week, STEM Learning announced a set of new free resources to support teaching in these key areas.

The Artificial Intelligence resources include three different packages aimed at students of different ages.


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Are indie games better value than AAA games?

Sunday, June 23rd, 2019

This post started life as a debate with friends about whether big triple-A games are better value than cheaper indie games. We didn’t have data, the debate was just opinions. But it stuck with me, so I decided to collect data to prove I was right. 🙂

The plan was to plot time I spend playing games against how much money I spent on them, and use the clear correlation to prove my point. That didn’t work. I didn’t find much of a pattern, but it’s been a while since I’ve done this sort of quantified-self thing and collecting the data was a pain so I’m sharing it anyway!

To start with, this graph plots the cost of each game (x axis) against the number of hours I’ve spent playing them (y axis).


Cost against Hours played – click for larger version

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Machine Learning for Kids outage report

Wednesday, May 30th, 2018

Machine Learning for Kids was unavailable for most of 29th May 2018. I wanted to share what happened and what I’m doing about it.

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