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Lecture 2: Supervised Learning and Representations
Автор: Logan Ward
Загружено: 2021-10-10
Просмотров: 590
Описание:
This is a theory-heavy lecture that covers an important concept in AI in science: how to encode scientific knowledge into the models being learned. The lecture touches on the variety of schools of thought around representations, how they related to building machine learning models, and the pros and cons of each approach.
PSA: Representations are a subject I wrote my PhD about, so I have a fair amount to say about this.
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