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| | matthewmcateer.me
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| | Important mathematical prerequisites for getting into Machine Learning, Deep Learning, or any of the other space
| | www.randomservices.org
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| | [AI summary] The text presents a comprehensive overview of the beta-Bernoulli process and its related statistical properties. Key concepts include: 1) The Bayesian estimator of the probability parameter $ p $ based on Bernoulli trials, which is $ rac{a + Y_n}{a + b + n} $, where $ a $ and $ b $ are parameters of the beta distribution. 2) The stochastic process $ s{Z} = rac{a + Y_n}{a + b + n} $, which is a martingale and central to the theory of the beta-Bernoulli process. 3) The distribution of the trial number of the $ k $th success, $ V_k $, which follows a beta-negative binomial distribution. 4) The mean and variance of $ V_k $, derived using conditional expectations. 5) The connection between the beta distribution and the negative binomial distributi...
| | rgoswami.me
5.2 parsecs away

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| | Setup details are described here, and the meta-post about these solutions is here. Materials The summmer course1 is based off of the second edition of Statistical Rethinking by Richard McElreath. Chapter 13 E{1,2,3,4,5} Chapter 14 E{1,2,3} Packages A colophon with details is provided at the end, but the following packages and theme parameters are used throughout. 1libsUsed<-c("tidyverse","tidybayes","orgutils","dagitty", 2 "rethinking","tidybayes.rethinking", 3 "ggplot2","kableExtra","dplyr","glue", 4 "latex2exp","data.table","printr","devtools") 5invisible(lapply(libsUsed, library, character.only = TRUE)); 6theme_set(theme_grey(base_size=24)) 7set.seed(1995) Chapter XIII: Models With Memory Easy Questions (Ch13) HOLD 13E1 Which of the following priors will ...
| | www.pbs.org
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| Former President Donald Trump has been indicted on four felony counts, including conspiracy to defraud the United States and witness tampering, for his efforts to overturn the 2020 presidential election.