It’s half-term week, so that means more time for geekiness with the kids.
This is something Grace made this week: a game of “I spy” built using Scratch, that uses the Watson Vision Recognition API to let the game dynamically pick objects that it recognises in photos, so you can then make guesses.
Apart from being a fun game to make in it’s own right, I wanted to share why I particularly think it’s useful to be able to use Watson API’s from Scratch projects.
It’s basically Top Trumps: that card game I used to play as a kid where you choose one of the attributes on a card, and if it beats the other player you get their card. Except it’s online, and you’re playing against a computer.
But the computer hasn’t been given any strategies on how to play, and has to learn from the player.
Initially, it makes random choices, but it learns from playing against the player. The more turns it plays, the more training it gets, which it uses to make predictions of which choice would give it the best chance of winning. Read the rest of this entry »
A simple hands-on activity to let kids train a machine learning classifier to be able to play Rock, Paper, Scissors.
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.