I recently wrote an email to an Irish Entrepreneur about the challenges of using Kubernetes and Kafka. I think both technologies are awesome, but I’ve seen in the past companies trying to integrate them without thinking about the managed services that exist out there. Kubernetes If you’re doing it yourself I’d look at https://docs.aws.amazon.com/eks/latest/userguide/getting-started.html which is from… Continue reading Why serverless matters or how do you want to spend your innovation tokens?
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”
I’ve got an online course called Probabilistic Programming Primer You may be wondering what that’s all about, so I put together a video explainer all about it. Building easy to interpret models isn’t a nice to have anymore it is the reason people pay for models in the first place. And as we see more… Continue reading Introduction to Probabilistic Programming Primer
I recently put together a survey of over 100 data scientists and analysts. There’ll be a report coming super soon, but before then I wanted to share the infographic. We’ll go into more detail in the report. If you’d like to get access to the report you should sign up here 70 percent of data scientists… Continue reading State of PPL: How are Bayesian methods used in industry?
(Repost from 2015) I recently interviewed Hadley Wickham the creator of Ggplot2 and a famous R Stats person. He works for RStudio and his job is to work on Open Source software aimed at Data Geeks. Hadley is famous for his contributions to Data Science tooling and inspires a lot of other languages! I include some light edits. 1.… Continue reading Interview with a Data Scientist (Hadley Wickham)
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
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
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?