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A short class with Sarah and her students. The other ways are under More.
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Today, we will discuss how to create a basic AI model. This helps us understand how machines learn patterns from data! Can anyone tell me what AI stands for?
Artificial Intelligence!
Correct! Remember, AI is all about teaching computers to learn and make decisions based on data. Let’s explore the tools we’ll use.
For our models, we can work with images, sounds, or text data. What do you think is the most exciting aspect of choosing a data type?
I think using sound could be fun because we can make a music classifier!
Images must be cool too, like recognizing different animals!
Great ideas! Each data type has unique challenges and learning opportunities. Let’s move on and discuss how to collect this data.
Once we have our data, the next step is to train our model. Can anyone share what they think training means in AI?
I believe it means teaching the AI to recognize patterns or make decisions based on the data it sees!
Exactly! The model learns from the data to make predictions. After training, we need to test the model's performance. Who knows why that is important?
To see if it works correctly and make improvements!
Exactly right! Let’s see how we can refine our models before sharing our outcomes.
Lastly, we want to present our findings. What do you think is key to a good presentation of your AI model?
Showing how it works and what it learned!
And maybe showing examples of correct and incorrect predictions!
Great points! Sharing your learning journey is important. Let’s recap what we learned today!
To train and test with great zest, your AI will ace the data quest!
Once there was an AI named Artie who learned to see pictures and listen to sounds, leading to a discovery that made everyone smile!
Choose, Collect, Train, Test, and Tell – CCTT!
CRUD - Collect, Refine, Understand, Deliver!
Term
What is AI?
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What is training in AI?
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What is a dataset?
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What is testing in AI?
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The simulation of human intelligence processes by machines, particularly computer systems.
The format in which data is stored, such as images, text, or sound.
The process of teaching an AI model to recognize patterns in data.
Evaluating the performance of an AI model on unseen data.
A collection of data used for training or testing an AI model.
This section guides students in creating a basic AI model using accessible tools, emphasizing learning through practical application.
Students will engage in hands-on AI modeling, learning key concepts like data types and the training/testing processes through user-friendly resources. The project fosters creativity and problem-solving aligned with real-world applications.
In this section, students will learn how to create a basic artificial intelligence (AI) model using intuitive tools designed for beginners, helping them grasp fundamental AI concepts, including how machines learn from data, the significance of datasets, and the processes of training and testing models.
Students will explore tools like Teachable Machine, ideal for training models with images, sounds, or poses, and Machine Learning for Kids, which allows for model creation using texts and images with applications in Scratch or Python.
This project not only enhances practical understanding of AI but also aligns activities with the Sustainable Development Goals (SDGs), fostering teamwork, innovation, and real-world problem-solving.