Gradient descent on a Softmax cross-entropy cost function
In this blog post, you will learn how to implement gradient descent on a linear classifier with a Softmax cross-entropy loss function. I recently had to implement this from scratch, during the CS231 course offered by Stanford on visual recognition. Andrej
madalinabuzau.github.io
위 블로그에 정리된 증명을 통해 과정을 납득할 수 있었다.
아직 벡터(텐서)나 매트릭스의 미분에 익숙하지 않은 것 같아 관련 예제들을 집중하며 봐야겠다.
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