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adl1995.github.io | ||
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yasha.solutions
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| | | | | A loss function, also known as a cost function or objective function, is a critical component in training machine learning models, particularly in neural networks and deep learning... | |
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michael-lewis.com
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| | | | | This is a short summary of some of the terminology used in machine learning, with an emphasis on neural networks. I've put it together primarily to help my own understanding, phrasing it largely in non-mathematical terms. As such it may be of use to others who come from more of a programming than a mathematical background. | |
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programmathically.com
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| | | | | Sharing is caringTweetIn this post, we develop an understanding of why gradients can vanish or explode when training deep neural networks. Furthermore, we look at some strategies for avoiding exploding and vanishing gradients. The vanishing gradient problem describes a situation encountered in the training of neural networks where the gradients used to update the weights [] | |
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utkuufuk.com
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| | | Previously, we talked about how to build a binary classifier by implementing our own logistic regression model in Python. In this post, we're going to build upon that existing model and turn it into a | ||
