Archive for the ‘ibm’ Category

Can computers be creative?

Wednesday, October 25th, 2017

from: https://tv.theiet.org/?videoid=10995

Machine Learning for Kids event at Hursley

Wednesday, August 30th, 2017

On Tuesday, a couple of dozen children (aged 8-14) spent the afternoon at Hursley so I could give them an intro to machine learning using some of the activities I’ve written for machinelearningforkids.co.uk.

I think it went pretty well, so I thought it’d be good to share what we did.


This was what the room looked like before the kids arrived… with just my two kids helping me set up. It all got a lot busier after this!

The general approach was letting them all work at computers, guided by a worksheet to build something that illustrated an aspect of machine learning. And then following this with a group discussion to draw out what they observed and what it meant.

We did this all together for the first couple of activities. Because of the large age range in the group, after this I let them split up and tackle different activities at different speeds, and followed this up by discussing their projects with them in smaller groups.

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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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