Archive for the ‘ibm’ Category

MachineLearningForKids.co.uk

Wednesday, August 2nd, 2017

I’d like to introduce “Machine Learning for Kids“: a tool to help school children learn about machine learning by making things with it.

The video above is a walkthrough of the tool and examples of how I’ve been using it. The rest of this post is a transcript for the video.

machinelearningforkids.co.uk is a simple tool for training a variety of types of machine learning model, and an environment for creating games and other interactive projects that use them.

This is done by extending Scratch: a visual programming environment created to teach coding to kids, that is widely used in schools and other educational organisations like Code Club and Girls Who Code.

It gives students a blank canvas without prescribing what they make. They’re free to use their imagination and creativity to find fun uses for the machine learning models that they train.

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Introducing Machine Learning to kids

Tuesday, July 4th, 2017

Today, I was helping out with a Computing summer school for teachers in London.

As part of this, I gave a presentation about machine learning to a room full of school teachers – about what it is, why I think we should be introducing it in the classroom, and how I think we could do that.

My slides are on Slideshare, but they might not make a lot of sense by themselves, so I’ll jot down here roughly what I said.

slide 1

This morning I want to talk to you about machine learning. In particular, I want to talk with you about machine learning in the context of education and how it could be introduced in the classroom.

slide 2

I’m going to try and cover three main points.

Firstly, a quick level set on what I mean by machine learning.
Then I’d like to talk about why I believe it’s important that we do this.
Finally, I want to talk about the practicalities of how we could effectively introduce machine learning in an accessible way.

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weatherbot

Sunday, April 23rd, 2017

TJBot is an open-source do-it-yourself kit for building a small Raspberry-Pi-powered robot.

Building

In the Easter holidays, we spent an afternoon building it…

…and wiring it…

This gave us a tiny plastic robot with a light in his head, and an arm that can rotate back and forth. He sits on the kitchen shelf next to the Alexa.

This weekend, we tried doing something with it.

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Owlbot: Faith’s first chatbot (and barcamp)

Sunday, November 13th, 2016

For her talk at Barcamp Southampton yesterday, Faith did a presentation on owls, together with a chatbot she trained to answer questions about owls.

I’ve brought Grace to a couple of barcamps with me before: Barcamp Berkshire and Barcamp Bournemouth. But this was Faith’s first time.

She decided that she wanted to do a talk on owls. That wasn’t a big surprise… she’s a little bit obsessed with owls.

Some of Faith's owls

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Normalised Discounted Cumulative Gain

Friday, July 15th, 2016

A ramble about accuracy compared with NDCG scores for evaluating effectiveness of information retrieval. It’s an introduction, so if you already know what they are, you can skip this.

A couple of weeks ago, we released a new tool for training the IBM Watson Retrieve and Rank service (a search service that uses machine learning to train it how to sort search results into the best order).

This afternoon, I deployed a collection of small updates to the tool and thought I’d make a few notes about what’s changed.

Most of them are a bunch of incremental updates and minor bug fixes.

For example, support for a wider range of Bluemix environments, support for larger document cluster sizes, displaying the amount of disk space left in a cluster, and so on.

One update in particular I thought was more interesting, and worth explaining.

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IBM Watson Retrieve and Rank tool

Thursday, June 30th, 2016

A few months ago, I mentioned that I was starting a new project. In this post, I’ll explain what we’ve been working on and what we’re trying to achieve with it.

The project was to build something new: a self-serve web-based tool to enable training the IBM Watson Retrieve and Rank service.

Earlier today, we released a first version of the tool. Now it’s finally out there, I can share what I’ve been working on!


My video walkthrough of the IBM Watson Retrieve and Rank tool

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Watson Rock, Paper, Scissors

Sunday, June 26th, 2016

A simple hands-on activity to let kids train a machine learning classifier to be able to play Rock, Paper, Scissors.

Screen Shot 2016-06-26 at 13.59.20

I’ve written and spoken before that I think we should do more to introduce children to the idea of machine learning. And I’ve tried introducing my two kids to it, such as by making a Code Club-style game with them: we built a system to play Guess Who, that they trained both to understand what you say and to recognise the characteristics of faces from photos.

This weekend, we tried out another idea – Rock, Paper, Scissors from a web app, using the web cam to see your moves, and training a system to recognise your hand signs.

DSC06146

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An introduction to machine learning with Guess Who

Thursday, February 18th, 2016

I tried introducing my two kids to machine learning by helping them make a game this week.

In this post, I’ll try and explain why, how we did it, and how it went. And if you make it all the way to an end, I’ve got some videos and a link to a demo to show you what we made.

Why

I think we need to introduce the basic concept of machine learning to children.

I think the current approach to introducing coding using things like Scratch aren’t enough. This isn’t to say Scratch isn’t great (I’ve been running a Code Club every week for the last couple of years, delivered almost entirely using Scratch, so I’d be the last person to say it isn’t a fantastic tool). It lets you snap together blocks representing actions to teach the programming mindset of getting a computer to do something by you breaking the task down into a series of steps.

I think we need to add to this with something that introduces the model of machine learning – getting a computer to do something by training it with examples of doing that task.

I’ve been saying this for a while – I gave a talk about it at an education conference last year, I’ve written about it here before, and it was the theme of a lecture I gave at a science society in London last month.

This week is half-term and I have the week off work, so I thought I’d finally spend a bit of time trying it out by experimenting on my own two daughters (Faith and Grace, who are aged 7 and 11).

In Code Club, I mostly try to introduce programming concepts by helping the kids to create games. Sticking with what seems to work, I’ve helped them to make a game by training an ML system how to play it.

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