https://towardsdatascience.com/on-bayesian-geometry-7755abf9f4d2 On Bayesian GeometryGeometric interpretation of probability distributionsMichael Larionov, PhD “Bayesian inference is based on the fact that we often don’t know the underlying distribution of data, so we need
What I Read: How to assign partial credit on an exam of true-false questions
https://terrytao.wordpress.com/2016/06/01/how-to-assign-partial-credit-on-an-exam-of-true-false-questions/ How to assign partial credit on an exam of true-false questions?By Terence Tao1 June, 2016Updates on my research and expository papers, discussion of open problems, and other maths-related topics.
What I Read: binary cross-entropy, log loss
https://towardsdatascience.com/understanding-binary-cross-entropy-log-loss-a-visual-explanation-a3ac6025181a?gi=375ce73be21b Understanding binary cross-entropy / log loss: a visual explanationDaniel GodoyNov 21, 2018 “If you are training a binary classifier, chances are you are using binary cross-entropy / log loss
What I Read: data distributions
https://www.kdnuggets.com/2020/06/overview-data-distributions.html Overview of data distributionsTags: Binomial, Distribution, Normal Distribution, Poisson Distribution, Probability, StatisticsBy Madalina Ciortan, Data scientist, PhD researcher in bioinformatics at ULB “With so many types of data distributions
What I Watch: Probabilities of probabilities binomial
Which rating is better, mathematically speaking? | Probabilities of probabilities, part 1Mar 15, 20203Blue1Brown
What I Watch: Bayes theorem
Bayes theoremDec 22, 20193Blue1Brown “The goal is for you to come away from this video understanding one of the most important formulas in all of probability: Bayes theorem.”