Скачать или смотреть Log Softmax Explained with Python!

Log softmax is used to improve the numerical stability of softmax, let's see why with Python!

Table of Content
Introduction: 0:00
Softmax: 0:13
Problem Statement: 0:37
Problems with Softmax: 1:17
Try it out! : 3:40
Solution: 3:46
Code: 9:12
Torch Implementation: 10:43

Problem Statement:
"In machine learning and statistics, the softmax function is a generalization of the logistic function that converts a vector of scores into probabilities. The log-softmax function is the logarithm of the softmax function, and it is often used for numerical stability when computing the softmax of large numbers. Given a 1D numpy array of scores, implement a Python function to compute the log-softmax of the array."

Problem link:
📌 https://www.deep-ml.com/problem/Log%2...

Important Links:
📌 Exp Normalization Trick: https://timvieira.github.io/blog/post...

Torch implementation:
📌 https://github.com/pytorch/pytorch/bl...

3 Interesting Questions:
📌 https://stats.stackexchange.com/quest...
📌 https://datascience.stackexchange.com...
📌 https://stackoverflow.com/questions/6...

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