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chris-said.io | ||
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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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aosmith.rbind.io
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| | | | | When working with counts, having many zeros does not necessarily indicate zero inflation. I demonstrate this by simulating data from the negative binomial and generalized Poisson distributions. I then show one way to check if the data has excess zeros compared to the number of zeros expected based on the model. | |
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sebastianraschka.com
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| | | | | I'm Sebastian: a machine learning & AI researcher, programmer, and author. As Staff Research Engineer Lightning AI, I focus on the intersection of AI research, software development, and large language models (LLMs). | |
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www.r-spatial.org
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| | | Spatial networks in R with sf and tidygraphLucas van der Meer, Robin Lovelace & Lorena AbadSeptember 26, 2019 | ||
