What is machine learning?
Identify real-world examples of machine learning
Learn the three stages to machine learning: input data, model and prediciton
Machine learning bingo template (1-per student)
Pen/pencil & paper
Lesson 1 Slides
No prior knowledge of machine learning
Slides: Introduction (8-10 minutes)
* If you have not already, download the Google Slides for Lesson 1 pressing the "Slides" button at the top of the page before continuing.
The first 3 slides of the lesson introduce students to machine learning. The aim is to get students to learn that machine learning does not simply just mean futuristic robots but it is instead something that we interact with in our every day lives. Slide 3 gives a simple definition, saying that "Machine learning teaches computers to do human-like tasks".
Main Activity: Machine Learning Bingo (20 minutes)
* If you have not already, download the machine learning bingo template in the Lesson Materials.
Each students should be given one blank machine learning bingo template (1-per student). This main activity gets students to actively interact with their peers to find examples of machine learning that they interact with in their every day lives. Each square contains examples such as "Seen Netfflix recommended movies and TV shows" or "Used FaceID to unlock a smartphone".
EXAMPLE MACHINE LEARNING BINGO TEMPLATE:
The aim of the task is for students to walk around the classroom speaking with their classmates and to fill in squares within the bingo template. Every time a student says that they have done or seen one of the machine learning examples in the grid, they mark a tally against that grid square. The activity is complete when the first student to gets a full row, diagonal or column all filled in (feel free to make the challenge easier or harder depening on number of students in class).
Discussion (5 minutes)
Once the machine learning bingo main activity is complete, get students to discuss their findings - what was the most popular grid square? Ask for more findings from the students, there is a blank page on slide 6 to write down answers on an interactive whiteboard (if this is beneficial).
Slides: Three steps to Machine Learning (15 minutes)
After the discussion, go back to the slides and complete the remaining lesson. The following slides go into further depth of machine learning and introduce students to the three stages of machine learning algorithm: input data, model and prediction. Input data can be in multiple formats, such as images, tv shows, text messages. The model is used to find patterns within the data - for example, what how does Netflix know what movies and TV shows to recommend? Netflix uses machine learning to find patterns within your viewing history. The model might learn that a user likes a certain movie genre - e.g. comedy. Finally, the model then makes a prediction. So given a user that likes comedy movies, the Netflix recommendation machine learning model will recommend more comedy films.
Machine Learning Example - FaceID
Apple's FaceID uses machine learning to unlock users phones. The input data in this case is images of a users face in different angles - looking up, down, left and right. The model then learns what a user looks like - shape of their nose, mouth, cheek bones, etc. Finally, the prediction determines whether or not to unlock the phone - if the user identity is verified "unlock", if not "lock".