Machine learning is all around us. We all use machine learning systems every day – such as spam filters, recommendation engines, language translation services, chatbots and digital assistants, search engines, and fraud detection systems.
It will soon be normal for machine learning systems to drive our cars, and help doctors to diagnose and treat our illnesses.
By exposing themselves to a new field like Machine Learning at this very young age gives them an understanding of how computers visualize and interpret data. They will start learning that computers and smartphones aren’t just a device to play games but they have a useful way of doing things and they can be taught to do specific things.
It’s important that kids are aware of how our world works. The best way to understand the capabilities and implications is to be able to build with this technology for themselves.
What is Machine learning?
Tom M Mitchell well know ML expert states that “Machine learning is the study of computer algorithms that allow computer programs to automatically improve through experience.”
In Simple Terms
A computer program can learn and adapt to new data without human interference.
How to even get started?
Learn Scratch – My eight-year-old Manasi just knows anything else about computers other than playing games, ms painting and just typing on keyboards. She got exposure to Scratch 3.0 during her covid-19 holidays.
Scratch is a block-based visual programming language and website targeted primarily at children. Users of the site can create online projects using a block-like interface. The service is developed by the MIT Media Lab, has been translated into 70+ languages, and is used in most parts of the world. Scratch is taught and used in after-school centers, schools, and colleges, as well as other public knowledge institutions.
Here’s a walkthrough of Machine Learning for Kids and examples of the projects:
The Best Place to Start: Dale Lane’s MachineLearningForKids.co.uk
This free tool introduces machine learning by providing hands-on experiences for training machine learning systems and building things with them.
It provides an easy-to-use guided environment for training machine learning models to recognise text, numbers, images, or sounds.
This builds on existing efforts to introduce and teach coding to children, by adding these models to educational coding platforms Scratch and App Inventor, and helping children create projects and build games with the machine learning models they train.
The tool was first made available in 2017, and is now being used by thousands of schools, code clubs, and families around the world.
Machine Learning for Kids is a useful tool for introducing children to how ML systems are trained, how they are used, and some of the real-world implications of AI applications.
Machine learning for kids using Scratch Step-by-step
STEP 1 : Go to https://machinelearningforkids.co.uk/ and click on Get Started button. You will get three options on the next screen:
a.) Sign Up — If you are a first time user, it is recommended to register, reasons being:
- You can work with images like face recognition
- Ability to save and load the projects
- Ability to create multiple projects
- Collaborate with other kids
b.) Already registered – You can login with credentials
c.) Try without registering – Without providing credentials tool allows to create projects with restrictions
STEP 2. Using Scratch (available on the site), we are going to create a “Smart classroom” when you type switch on Light it will light up similarly if you type in command switch on Fan it is hot fan will be on. You will be able to find in-depth tutorial for this and several other interesting exercises under Worksheets section.
STEP 3. Login using your userID and password or just click on Try it now button.
STEP 4. In the next screen, click on Add a new project button — you are going to create a new Scratch project now.
STEP 5. Provide project name as “Smart ClassRoom” and in the dropdown — Recognizing, choose text and click on Create button. This dropdown associates the type of machine learning aspect with your Scratch project. There are 4 types of Machine learning projects one can do:
a.) Text — make the computer learn specific text patterns, sentiment analysis and have a simple conversation
b.) Images — make the computer to identify people’s faces, objects, handwriting
c.) Numbers — logistic regression, number patterns etc
d.) Sounds — make the computer identify specific sounds, voices, speech recognition, music
STEP 6. Click on the project name to work on this project.
STEP 7. The next screen has 3 buttons:
- Train — Collect examples of what you want the computer to recognize
- Learn & Test — Use the examples to train the computer to recognize text
- Make — Use the machine learning model you’ve trained to make a game or app, in Scratch or in Python
STEP 8. Now click on the Train button. Add four labels as in the below screenshot and add as many examples as you can for both the labels.
STEP 9. Click on Back to Project on top left corner and click on Learn & Test button. Now we are going to train it, during this process it learns using the given words if a given message is mean or kind. To do this, simply click the button Train new machine learning model button.
STEP 10. Usually, it will take a while till it trains the model.
A model in AI is a formula that takes input(s) and produces output(s).
STEP 11. Once it is ready it will display Available from Training state.
STEP 12. Next, click on Back to Project button and on the next screen, click on Make button. It gives below choices:
- Scratch — Make a project in the old version of Scratch 2.0
- Scratch 3 — Use the new version of Scratch 3.0
- Python — Write Python code to use your machine learning model
- App Inventor — Make a mobile app for your phone or tablet The model can be used here to create your own app
STEP 13. For this tutorial since we are doing through scratch click on Scratch 3 — this opens the Scratch window. Then click on Project Templates and select Smart ClassRoom
STEP 14. Create the following script:
STEP 15. Now save and click on green flag to run the script. It will ask “Enter your command”
STEP 16. If you type it is too hot it will switch on the fan similarly if you type the command its too dark it will switch on the light all these are trained from the Label data with examples earlier.
STEP 17. Click on the green flag and test again few more commands.
FINAL TIP: The more examples you give it to learn with, the better it will be. The more examples you use to train the machine learning model, the better your program should get at recognizing commands.
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