How Machines Learn
Learning Objective
Students will understand the general concepts of how a machine/computer can learn using pattern recognition and math
Lesson Flow
Watch Video
How does artificial intelligence learn? - Briana Brownell
TED-Ed
Guided Notes
Key concepts students will learn:
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The three basic types of machine learning are unsupervised learning, supervised learning, and reinforcement learning.
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Unsupervised learning is useful for finding general similarities and patterns, while supervised learning requires active input from doctors and computer scientists to improve accuracy.
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Reinforcement learning uses an iterative approach to gather feedback and create optimal plans, and artificial neural networks can use millions of connections to tackle difficult tasks.
Practice
8 questions • Multiple choice & Short answer
Exit Ticket
“Describe one of the three types of machine learning (unsupervised, supervised, or reinforcement) discussed in the video, explaining how it uses pattern recognition and math to learn.”
Teacher Guide
Get the complete package:
- Answer keys for all questions
- Differentiation strategies
- Extension activities
- Printable student handouts
