These activities use Google Teachable Machine to create machine learning models that students can incorporate into their Snap! programs. These models are quick to create online but will enable students to develop some intuition for how machine learning works and how it depends on the data that they use to create it. In each activity, students will create and test a machine learning model and then use it in a Snap! program. The mathematics behind such models can be very complicated, but this activity will use a simplified model to give students an idea of what is happening “behind the scenes” in machine learning.
Please note that these activities are designed to be completed in number order. Because of this, Activity 1: Image Recognition has the most detail, and is referenced in the other activities.
These activities use Google Teachable Machine to create machine learning models that students can incorporate into their Python programs. These models are quick to create online but will enable students to develop some intuition for how machine learning works and how it depends on the data that they use to create it. In each activity, students will create and test a machine learning model and then use it in a Python program. The mathematics behind such models can be very complicated, but this activity will use a simplified model to give students an idea of what is happening “behind the scenes” in machine learning.
Please note that these activities are designed to be completed in number order. Because of this, Activity 1: Image Recognition has the most detail, and is referenced in the other activities.
Control the Finch Robot with a magic wand!
In this activity, students will create a gesture recognition model to recognize motion patterns on a micro:bit attached to a “magic wand”. Students will then create a program that makes the Finch Robot react to the different motions using radio communication between the two micro:bits.
We would like to acknowledge the work of Ken Kahn and Jens Moenig. Ken’s Snap! project for machine learning was used as a reference when developing Activities 1-3, and Jens’ video tutorial is the basis for Activity 4.
