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This is an episodic podcast, so you can listen to it in any order, but episode one is a great place to start.
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We break down supervised learning, explaining how AI learns from labeled examples just like how children learn from teachers identifying objects.
• Supervised learning is when AI learns from labeled examples (like seeing pictures of apples with labels)
• The more examples an AI sees, the better it gets at recognizing patterns
• Real-world applications include Google Lens, spam filters, AI art apps, and medical diagnostic tools
• Bad or confusing data leads to incorrect learning outcomes
• AI can struggle with examples it hasn't seen before (like only recognizing yellow cats but not black ones)
• Try the "Label It Game" at home using pictures from magazines or your own drawings
• Experiment with Google's Teachable Machine website to train your own mini AI model
Join us next time for the letter T in our ABCs of AI series!
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