@MLforKids

Introducing kids to machine learning using Scratch, Python and App Inventor (account run by @dalelane)

 UK
machinelearningforkids.co.uk
Joined April 2017
  • Tweets288
  • Following328
  • Followers2.6K
119Media
Machine Learning for Kids: helping kids learn about ML by letting them train models and make things with them Info at machinelearningforkids.co.uk
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Make a AI-powered traffic camera game in #Scratch, where you have to train a #machinelearning model to recognise if there are passengers in the car. Full instructions at machinelearningforkids.co.uk…
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A new feature was added to @MLforKids this week by @all_about_code - integration with EduBlocks! 🎉🎊 This will let students create machine learning Python projects in the browser, by dragging and dropping blocks on a canvas. dalelane.co.uk/blog/?p=4899

Machine Learning for Kids with EduBlocks

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...

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The recording from my talk at @Heapconf has been posted - the idea of the talk was to share stories of #artificialintelliegence lessons I’ve run in schools. The focus of the talk was how I've seen children understand and react to #machinelearning dalelane.co.uk/blog/?p=4871

What children can learn about artificial intelligence

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...

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ML for Kids retweeted
CintichuEF@cintichuEF6 May 2023
Replying to @chusca14 @sandboxeduca @rafabillor @genially_es
Estoy haciendo un curso de: DESCUBRE LA INTELIGENCIA ARTIFICIAL IBM: Machine Learning for Kids. También incluye Scratch 3. El curso nos lo ofertan desde la plataforma de innovación de la comunidad de Madrid.
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Creating projects based on real-world applications of #machinelearning is an effective way to open up students' eyes to the fact that AI systems are all around them, and impact their lives in countless ways machinelearningforkids.co.uk…

Invisible artificial intelligence systems are everywhere

Creating projects based on real-world applications of machine learning is an effective way to open up students' eyes to the fact that AI systems are all around them, and impact their lives in...

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EXCITING NEWS 🎉 Experience AI launches today in partnership with @DeepMind. Our new AI and machine learning programme for teachers, students, and other educators. Find out more 👉 rpf.io/experienceai23 #AI #MachineLearning #DeepMind #ExperienceAI
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Make a #machinelearning-powered "I Spy" game in #Scratch, where you have to guess what the AI has recognised in a photo Full instructions at machinelearningforkids.co.uk…
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School students are able to engage in debates about the ways that artificial intelligence tech is used. This can be helped giving them a hands-on chance to experiment with the tech and see for themselves how bias can be introduced. machinelearningforkids.co.uk…

Bias and the responsibility of the machine learning developer

By experimenting with their own machine learning model, students can see how easy it is to introduce bias into AI applications - which enables them to engage in debates on ethics in AI.

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Some of the most effective #machinelearning lessons are when something goes a bit wrong. The discussions this enables really helps students understand how ML behaves. Here's one example of how that can go... machinelearningforkids.co.uk…

Inputs that aren't represented in training may not be recognised correctly

When students train a machine learning model to do one thing, they can see how it might not be very good at doing a different thing.

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Allowing students to experiment in a child-friendly sandbox can help them to understand how #MachineLearning doesn't always learn what we wanted it to learn! Here are a couple examples of how I've seen this go... machinelearningforkids.co.uk…

Machine learning doesn't always learn what we intend it to

Machine learning models learn from patterns in the training data that we give them, whether or not those are patterns we'd intended to give.

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The flexibility of #Scratch provides students with opportunities to explore the behaviour of #MachineLearning models in creative ways - such as how to deal with machine learning tech being a black box. machinelearningforkids.co.uk…

There are ways to deal with the 'black box challenge'

The flexibility of blocks in Scratch provide students with opportunities to explore the behaviour of machine learning models in creative ways.

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Students can learn a lot about the role of confidence scores through playing and experimenting with their own simple #machinelearning models - some of the ways children will describe this are fantastic machinelearningforkids.co.uk…

How to use confidence scores

Students learn how to effectively use confidence scores returned by machine learning models by playing, experimenting, and seeing the difference that different confidence thresholds make.

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The experiences students get by making their own #machinelearning projects helps them understand the behaviours and motivations of big tech companies. This is one of my favourite examples: machinelearningforkids.co.uk…

Collecting poorly handled inputs to add to training is a common practice

First-hand experience with machine learning technologies gives students a crucial insight into the behaviour and motivations of tech companies.

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Sentiment analysis projects are a nice way to show students that machine learning can learn to recognize a variety of types of patterns in text, not just the meaning or intent of the text. machinelearningforkids.co.uk…

Machine learning can learn to recognize different types of patterns

Machine learning can learn to recognize a wide variety of types of patterns in text, not just the meaning or intent of the text.

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Making simple #machinelearning projects introduces students to the idea of keeping training and test data separate machinelearningforkids.co.uk…

Training and test data should be kept separate

Machine learning projects need to keep training and test data separate.

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letting students try each other's #machinelearning projects allows them to notice for themselves how ML models trained with a wider variety of training examples perform better machinelearningforkids.co.uk…

Increasing diversity of training data often improves accuracy

Letting students try each other's project allows them to see that machine learning models trained with a wider variety of training examples perform better.

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Students can see for themselves why crowd-sourcing and gamification are used to help create training data for #machinelearning projects machinelearningforkids.co.uk…

Crowdsourcing and gamification can help to generate training data

Students can see for themselves how gamification is a great way to motivate people to create a lot of training data, and how crowd-sourcing the generation of training data is a great way to more...

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Giving students freedom to experiment with their own machine learning model lets them learn for themselves the relationship between the quantity of training data and the accuracy of machine learning models. machinelearningforkids.co.uk…

Collecting more training examples often improves accuracy

Giving students the freedom to experiment with their machine learning model lets them learn for themselves about the relationship between the quantity of training data and the accuracy of machine...

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Going through the process of creating a #machinelearning project for themselves gives students an insight into how these systems are created in the real world. machinelearningforkids.co.uk…

Workflow of a machine learning project

Going through the process of creating a machine learning project for themselves gives students an insight into how these systems are created in the real world.

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Using existing tools like #Scratch and #AppInventor to introduce students to #machinelearning was a conscious choice - to send a message that it complements what they already learn about coding machinelearningforkids.co.uk…

Machine learning hasn't replaced the need to learn to code

Building with ML in an existing sandbox like Scratch makes it clear that ML isn't separate to, or a replacement for, coding.

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