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healthyinfluence.com | ||
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andrewpwheeler.com
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| | | | | The default hypothesis tests that software spits out when you run a regression model is the null that the coefficient equals zero. Frequently there are other more interesting tests though, and this is one I've come across often -- testing whether two coefficients are equal to one another. The big point to remember is that... | |
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gameswithwords.fieldofscience.com
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| | | | | In this week's New Yorker , Jonah Lehrer shows once again just how hard it is to do good science journalism if you are not yourself a scient... | |
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ruqinren.wordpress.com
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| | | | | (Note that this post's content mainly comes from this wonderful summary blog elsewhere. I am replicating one part of the analysis here, and enhanced the content with some R code for easy implementation.) Sometimes it is necessary for researchers to test not only the null hypothesis that beta = 0, but also that beta1 =... | |
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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 [] | ||
