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 ivelasq.rbind.io
Understanding the native R pipe |> - %>% dreams
| | kupac.gitlab.io
Maybe monad in R - Biofunctor
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| | [AI summary] The article introduces the concept of monads in the R programming language by implementing a simple 'Maybe' monad to handle errors and missing data robustly in data processing pipelines.
| | magrittr.tidyverse.org
Introducing magrittr magrittr
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| | rdrr.io
function: Function Definition
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| | teddykoker.com
Multi-Class Classification with Logistic Regression in Python | Teddy Koker
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| A few posts back I wrote about a common parameter optimization method known as Gradient Ascent. In this post we will see how a similar method can be used to create a model that can classify data. This time, instead of using gradient ascent to maximize a reward function, we will use gradient descent to minimize a cost function. Lets start by importing all the libraries we need: