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emiruz.com | ||
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www.jeremykun.com
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| | | | | Machine learning is broadly split into two camps, statistical learning and non-statistical learning. The latter we've started to get a good picture of on this blog; we approached Perceptrons, decision trees, and neural networks from a non-statistical perspective. And generally "statistical" learning is just that, a perspective. Data is phrased in terms of independent and dependent variables, and statistical techniques are leveraged against the data. In this post we'll focus on the simplest example of thi... | |
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svmiller.com
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| | | | | This is a basic tutorial for estimating the Poisson model, what it does, and how you should interpret what it tells you. | |
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aosmith.rbind.io
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| | | | | Extending my simulation examples into the world of generalized linear models, I simulate Poisson data to explore what a quadratic relationship looks like on the scale of the data when fitting a generalized linear model with a log link. | |
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ddarmon.github.io
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