I’ve been contributing on and off to PyMC3 and other projects for a few years now. I’m still learning a lot about Bayesian Statistics and building software. I intend to continue to work on this stuff. Chris Fonnesbeck – recently did a talk at NeurIPS where he talks about some of the stuff we’ve learned in… Continue reading 3 key lessons from being an OSS developer
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 saw recently this from the recent Amazon shareholder letter. “These big trends are not that hard to spot…We’re in the middle of an obvious one right now: machine learning & artificial intelligence” — Jeff Bezos One of the hard parts about working professionally on these technologies. Is I take them for granted. So I… Continue reading Working in a major trend – Machine Learning
I wrote my Masters Thesis on Probability inequalities. This short gist is some notes I wrote up to help me remember the basics of probability inequalities. You may find it useful.
Bio Brad Klingenberg is the Director of Styling Algorithms at Stitch Fix in San Francisco. His team uses data and algorithms to improve the selection of merchandise sent to clients. Prior to joining Stitch Fix Brad worked with data and predictive analytics at financial and technology companies. He studied applied mathematics at the University of… Continue reading Interview with a Data Scientist: Brad Klingenberg
Hilary Mason one of the shining lights of the world of data science Tweeted recently ‘Data people: What is the very first thing you do when you get your hands on a new data set?’ What I do when I get a new dataset is a recent article on the Simple Statistics blog, is a response… Continue reading Data Science as a Process
J.D.Long is the current AVP Risk Management at RenaissanceRe and has a 15 year history of working as an analytics professional. I sent him an interview recently to see what he would say. Good questions Peadar. Here’s a really fast attempt at answers: 1. What project have you worked on do you wish you could go back… Continue reading An interview with a data artisan
I once did an internship under Andrew Fogg at Import.io. I learned a lot about data science at that period, but one of the hardest lessons I had to learn was the importance of soft skills and project management in any data science projects. John Foreman another idol of mine, talked a bit about this,… Continue reading Data Science and Soft Skills
1. General state space Markov chains Most applications of Markov Chain Monte Carlo algorithms (MCMC) are concerned with continuous random variables, i.e the corresponding Markov chain has a continuous state space S. In this section we will give a brief overview of the theory underlying Markov chains with general state spaces. Although the basic principles… Continue reading Markov Chains and Monte Carlo Algorithms