Machine Learning for Kids

September 18, 2024

✨Get your champ ready for the disruptive future✨.

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Introduction to Machine Learning

Even though machine learning may seem complicated, it can be amusing and understandable to children when taught in the right manner. By familiarizing the young learners with the primary principles of machine learning, we enable them to be armed with the fundamental aptitudes required later in life. It also fosters affection for technology among them as they grow up while at the same time enabling them to think more critically and be creative. Let’s explore the possibility of making it sound like an exciting theme for young Gen Z and Gen Alpha.

What is Machine learning ?

Machine learning models with child's learning analogy

To make it simple. In the way this world works, a child is born and brought up in an environment where the child learns from what is being taught and also from the things that simply happen around them. Starting with speaking, moving in different ways, eating, etc., all the information around is fed to the 5 year old child’s brain, and it learns to return an output of the input information in the form of different things. In the case of a computer, it’s quite similar. We can feed a lot of data to a computer and use different machine-learning models to identify patterns in the data and learn. For example, we all get a lot of emails every day, some emails are useful and some are just there! if we want to sort those emails with different tags like Friends, Close friends, Workmates, promotions, etc. we can feed already sorted emails to the models, and that is called “Training data”. After the model is trained with this data, whenever you receive an email the model classifies it to the appropriate tag category, and voila! You've saved yourself some time.

Why teach Machine learning to kids ?

Reason behind learning machine learning and helping major industries break records!

Every parent has great aspirations for their children's career path and often find themselves thinking time and again about whether to choose this or that career approach, when a fresh mind learns computer science and programming languages, the most challenging habit to develop is computational thinking, which means how can you find a scalable solution to practical problems and serve your target audience. Machine learning is undoubtedly changing the world in numerous ways, including industries like Banking/Lending, Entertainment, Healthcare, Marketing/Advertising, Autonomous vehicles(i.e. Self driving cars), Retail, Energy and so much more. So if kids learn the fundamentals of machine learning well in advance, it would help them develop problem-solving skills, would help them be more productive and creative. hence young generation should adapt to this quickly

Examples of Kids Using AI/ML :-

The CEO Challenge: A show in India where high school kids use AI/ML to solve real-world problems and those with good ideas convert them into a business. (The link is available at the end of the article)
Global Initiatives: Kids worldwide are building AI projects, from climate change solutions to health tech, showing that in the ever-evolving world of technology, building isn’t limited to after college. (The link to a relative article is attached at the end of this article)

How to introduce Machine Learning to Kids?

In a nutshell ~ absolutely a fun way!

there are creative ways to ingrain machine learning in your children's lives, for instance, a kid can play fun computer games from a platform like Scratch(Link is attached at the end of this article) where they can visualize and learn fundamentals of Machine learning. If at all interest in coding develops in children they can make simple projects like an interactive chatbot friend or virtual assistant that speaks to the child in an easy and fun way via Code.org (Link is attached at the end of this article). And if you feel like a book is your way of learning things you can start with a friendly and easy-to-understand book like “Hello Ruby: Adventures in Coding” by Linda Liukas, all of these websites have their informational videos as "Tutorial for beginners" tailored for kids and it can help child . here's a quick look at how one such platform performs keep kids interested as they learn!

an illustration of project building and its UI

Kid-friendly Machine Learning example project to keep them interested!

Teach your computer to recognize cats and dogs! : open the link from the list at the end “Teachable Machine”, in the website click Get Started, choose the image project option, and create two classes 1) Cat and 2) Dog, now gather as many cats and dog pictures as possible and upload them to the relevant class (i.e. Cat pictures to the Cat class and Dog pictures to the Dog class) then click train model and Tada!! Your first classification project is ready, now test your project by uploading a new random photo of either a cat or a dog and see if it matches the True class!, this exercise will ingrain a basic understanding of Data collection and training models to predict on unseen data, giving them an initial touch of Real world Machine learning project.

Foundational Concepts of Machine Learning

Data Curation: Imagine you have a collection of toy cars and trucks. To teach your friends the difference, you first show them examples of each. Similarly, in machine learning, we collect and prepare data (like pictures of cats and dogs) to show (train) the computer.
Learning from Data: Just like you learn from practice and repetition, computers learn by looking at data. Computers improve their guesses on every iteration of training with new unseen data, just as you get better at recognizing different animals by seeing them repeatedly.
Loss Function: Think of this as a game where you guess the answer and get points based on how close you are. The computer tries to minimize its mistakes by improving its guesses, much like trying to get the highest score in a game.
Basic Algorithm (K-Nearest Neighbors): Imagine you are looking to join an additional tuition class for one of the subjects you wish to understand better, you have choices of joining many tuitions, but you are most likely to join the one that is nearby, just the same way as the name suggests, K- nearest neighbors algorithm works on distance function. This may not be a well-suited algorithm for a lot of use cases but isn't that a good reason to call the algorithm lazy!

Here's an image to depict how KNN Works~