Lecture
Inductive Bias in Machine Learning
Description
This lecture introduces the concept of inductive bias in machine learning, focusing on convolutional networks as a prime example. The slides cover the motivation behind convolutional networks, the success of deep neural networks in image tasks, the No Free-lunch Theorem, and different types of inductive bias. The instructor explains how inductive bias influences the learning process and the importance of prior knowledge in designing effective neural networks.
Official source
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