How machines and humans learn: from algorithms to motor skills
In short: Explore the fundamental principles of learning through the lens of artificial intelligence. This lecture moves from high-level concepts to specific algorithms, concluding with the biological realities of physical skill acquisition.
In this MIT OpenCourseWare lecture, instructor Patrick Winston introduces the core concepts of learning. The session provides a high-level overview before diving into the 'nearest neighbors' algorithm, utilizing various graphical examples to illustrate how data points can be categorized or predicted based on proximity.
The course then bridges the gap between machine learning and human biology by examining the acquisition of motor skills, specifically the act of bouncing a tennis ball. It further investigates the physiological constraints on learning by analyzing the impact of sleep deprivation on these processes.
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Sources
- Summary by Intellect · source: 10. Introduction to Learning, Nearest Neighbors
- Also: Lecture 10: Introduction to Learning, Nearest Neighbors | Artificial Intelligence | Electrical Engineering and Computer Science | MIT OpenCourseWare
- Also: Lecture 10: Introduction to Learning, Nearest Neighbors | MIT Learn
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