I recently caught up with Noelle Saldana and she shared some of her experiences as a Data Scientist and Product Management expert. She’s got a strong technical background and has worked for Pivotal a leading technology consultancy helping Forbes 500 learn how to leverage Machine Learning. She’s recently joined Salesforce where she’ll be wearing a… Continue reading “Much of our day-to-day lives are touched and improved by Data”
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
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
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?
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
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