Ai Mask detector

Introduction

• Introduce participants to the engineering design challenge 
• Explain what is image classification
• Discuss the ability and limitation of a machine to classify images.
• Introduce machine learning and give an example of the mask detector.
• Introduce a video about ML
• Discuss the use of AI in our daily lives.
• Introduce personal image classifier tool.
• Explain step by step how to train a model.

Share the tool link and ask them to create their own prototypes.

https://classifier.appinventor.mit.edu/

• Create labels
• Add pictures to train the model
• Testing their models.

Wrap up

• Ask participants to share their results and discuss how human bias plays a role in machine learning.

ask participants

•Can a computer recognize the photos and emotions like us?

•Is this hard or easy for a machine? 

ask

Have you heard about machine learning?

What do you know about machine learning?

What do you understand from the picture?

•Explain traditional programming and machine learning from the point of paper rock and scissor game.

•

•Say >> Instead of thinking all about of these rules and we have to write and express all of these rules in a code, what if we could provide a lot of answers and we could label those answers and then have a machine infer those rules

•Say >> For example, instead of writing a complicated code to describe the shape of a hand for the computer, we can just get a lot of images of people doing a rock so we can diverse hands, diverse skins, and tones. and then we just say to the machine hey this is what rock looks like, this is what a paper looks like. 

Examples from the video include:

•email filters

•auto-complete text

•video recommendation systems

•voice recognition

•translation apps

•digital assistants

•image recognition