From the course: Grasshopper: Generative Design for Architecture
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Introduction to machine learning
From the course: Grasshopper: Generative Design for Architecture
Introduction to machine learning
- [Voiceover] When we think of machine learning, perhaps we visualize self-driving cars or humanoid robots. Or maybe we think of some of the high profile achievements in machine learning systems. Competing with humans like Watson, winning at Jeopardy! Or AlphaGo beating the human Go champion Lee Sedol. These are the most technically sophisticated and computationally powerful examples of machine learning. Systems that took millions of dollars to design, train, and test. They are useful examples of the fundamental aspiration of machine learning to build generalized decision making and problem solving systems. Understand the principles and techniques underlying the pursuit of this aspiration may be more useful to consider machine learning at its simplest. Imagine I throw a ball in the air. In a second it comes back down on my head. Now I throw it 100 more times. Each time the ball lands on my head. Now, with a mild headache, I throw the ball in the air and raise my hands to catch it when…
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