GRADIENTS IN A DEEP NEURAL NETWORK AND THEIR PYTHON IMPLEMENTATIONS

  • Park, Young Ho
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초록

This is an expository article about the gradients in deep neural network. It is hard to find a place where gradients in a deep neural network are dealt in details in a systematic and mathematical way. We review and compute the gradients and Jacobians to derive formulas for gradients which appear in the backpropagation and implement them in vectorized forms in Python.

키워드

gradientsdeep neural networksbackpropagationsmachine learning
제목
GRADIENTS IN A DEEP NEURAL NETWORK AND THEIR PYTHON IMPLEMENTATIONS
저자
Park, Young Ho
DOI
10.11568/kjm.2022.30.1.131
발행일
2022
유형
Article
저널명
한국수학논문집
30
1
페이지
131 ~ 146