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In Chap. 3 we introduced linear regression, a linear model that learns a set of weights to apply to an input, in hopes of finding the model with the lowest error. However, linear models are limited in the behaviors that they can learn. In this chapter we learn about Neural Networks, a class of model that are capable of learning any possible function. We first introduce why Neural Networks are useful, then discuss how they are set up, trained, and used.

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Neural Networks—Introduction

  • 章节

  • 发表日期：

    2025年

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  • Matthew Guzdial,
  • Sam Snodgrass,
  • Adam Summerville

摘要

In Chap. 3 we introduced linear regression, a linear model that learns a set of weights to apply to an input, in hopes of finding the model with the lowest error. However, linear models are limited in the behaviors that they can learn. In this chapter we learn about Neural Networks, a class of model that are capable of learning any possible function. We first introduce why Neural Networks are useful, then discuss how they are set up, trained, and used.