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austinrochford.com | ||
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chipnetics.com
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| | | | | There is a lot to remember in data science! It touches everything from alignment, to data wranging, data analytics, storytelling and visuals. This python cheat sheet is a quick reference to get a fast boost into many of these areas. | |
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twiecki.io
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| | | | | [AI summary] This technical blog post explains the advantages of hierarchical Bayesian modeling over non-hierarchical approaches using a case study of predicting radon levels across different US counties with the PyMC3 library. | |
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teddykoker.com
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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: | |
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articles.foletta.org
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