ML for Kids

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

[ML for Kids @MLforKids]

Machine Learning for Kids: helping kids learn about ML by letting them train models and make things with them
Info at https://t.co/TzaNYhNy0G

[ML for Kids @MLforKids]

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 https://t.co/EDO6iqJouG

[ML for Kids @MLforKids]

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.
https://t.co/6qtTJviC11

[Dale Lane (inactive) @dalelane]

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

https://t.co/1teHMZGA3I

[CintichuEF @cintichuEF]

@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.

[ML for Kids @MLforKids]

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

https://t.co/VeWlGZ1ZUe

[Raspberry Pi Foundation @RaspberryPi_org]

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 👉 https://t.co/d5ot4tua4s

#AI #MachineLearning #DeepMind #ExperienceAI

[ML for Kids @MLforKids]

@amit_petro sorry - only just saw your message. The site is up now, and looking at the analytics history, I don't see any dips in the number of active users through the day that would suggest there was an outage. Are you able to access it now?

[ML for Kids @MLforKids]

@KaySawbridge no, sorry!

(I will be at https://t.co/izgpmqsFYC later this month though)

[ML for Kids @MLforKids]

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 https://t.co/EDO6iqJouG

[ML for Kids @MLforKids]

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.
https://t.co/dY58mEHtGx

[ML for Kids @MLforKids]

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...

https://t.co/SwgPekXy4T

[ML for Kids @MLforKids]

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...
https://t.co/DYh6R2EQR0

[ML for Kids @MLforKids]

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.

https://t.co/77ORKE07jn

[ML for Kids @MLforKids]

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
https://t.co/FBIwpF2yNm

[ML for Kids @MLforKids]

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:
https://t.co/8uNgotiASD

[ML for Kids @MLforKids]

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.
https://t.co/4fqr7k2WWu

[ML for Kids @MLforKids]

Making simple #machinelearning projects introduces students to the idea of keeping training and test data separate
https://t.co/S9nPheXoyW

[ML for Kids @MLforKids]

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

https://t.co/tTBMyLjaQF

[ML for Kids @MLforKids]

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

https://t.co/SyTuojtu5a

[ML for Kids @MLforKids]

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.
https://t.co/FhkIKWAQPx