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| | isaacslavitt.com
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| | [AI summary] The article discusses the German Tank Problem, a statistical estimation challenge where the goal is to infer the total number of tanks based on observed serial numbers, using Bayesian methods and MCMC libraries like Sampyl, PyMC3, and PyStan.
| | austinrochford.com
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| | .dataframe * {border-color: #c0c0c0 !important;} .dataframe th{background: #eee;} .dataframe td{ background: #fff; text-align: right; min-width:5em; } /* Format summary rows */ .datafram
| | 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...
| | www.v7labs.com
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| What are Generative Adversarial Networks and how do they work? Learn about GANs architecture and model training, and explore the most popular generative models variants and their limitations.