Bayesian Analysis the good parts One of the questions I’m often asked is what’s so powerful about Bayesian analysis? I speak regularly to analysts, who’ve heard of some of the powerful aspects of it, but haven’t heard enough to emotionally invest time in learning it. I’ve thought about this on and off for a few… Continue reading Think you need to learn Bayesian Analysis? Read this first
What is Bayesian Statistics Bayesian Statistics (or Probabilistic Programming) take a more effective and deep approach to perform analysis of any given data and situation. A/B testing is one of the hottest topics on the internet nowadays. In this testing, you simply consider two different groups, A and B, to analyze the performance of both… Continue reading 3 reasons to learn Bayesian Statistics in the new year
Bayesian Statistics and Supply Chain Supply Chain can be thought of as a set of procedures that are coordinated to combine manufacturers, suppliers, warehouses, and stores in order to ensure proper production and distribution of material of right quantities at the right location and in right time. This, in turn, ensures that the total supply… Continue reading Applications of Bayesian Statistics: Supply Chain
One question that is often asked by those who know Machine Learning to me is how do I build a Bayesian Logistic Regression model? If you know how to build a logistic regression model in sklearn or a standard machine learning library it’s quite easy to learn how to do the Bayesian version. In this screencast… Continue reading New Screencast: How do I build a Logistic Regression model the Bayesian way?
I recently gave a talk to the excellent research team at Signal Media. And got asked the question I didn’t want to be asked. It was what is the BFMI in PyMC3? The way I largely think of it is, in a practical level – which is – if the BFMI metric is below the… Continue reading What is BFMI (Bayesian Fraction of Missing Information)?
Probabilistic Programming versus Machine Learning In the past ten years, we’ve seen an explosion in Machine Learning applications, these applications have been particularly successful in search, e-commerce, advertising, social media and other verticals. These applications have been particularly focused on predictive accuracy and often involve large amounts of data — sometimes in the region of terabytes — in fact this… Continue reading Why would I ever NEED Bayesian Statistics?
I’ve been recently playing around with ‘arviz’. For those of you who don’t know Arviz is a library for exploratory analysis Bayesian Models. I’ve got a Bayesian model built – or someone has built one for me, how do I explore it? How do I plot it? This is the fundamental question that Arviz answers.… Continue reading How do I visualise the results of a Bayesian Model: Rugby models in Arviz
TLDR: This is an opinionated post, but based on recent trends. What is Probabilistic Programming? I recently wrote a course teaching this. Probabilistic Programming is a newish paradigm used in Quantitative Finance, Biology, Insurance and Sports Analytics – it allows you to build generative models to infer latent parameters and the uncertainty of those parameters. It’s been… Continue reading Why Probabilistic Programming is the next big thing in Data Science
Just a short blog post today. I wanted to write up some useful PyMC3 links I’ve found. https://eigenfoo.xyz/bayesian-modelling-cookbook/ — Great work by George Ho, who’s been contributing to PyMC3 recently. It’s a collection of tips I wished I had when I started out. https://discourse.pymc.io/ — This may be known to a lot of people –… Continue reading Bayesian Stats related links