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’m seeing a very fuzzy line between where technical business analysts end & IT teams begin. Y’all know of good articles/books on managing responsibilities when coding analysts on the biz side interface with IT dev teams? Seems tricky. #rstats #pydata #python — JD Long (@CMastication) October 19, 2018 My friend JD Long, has been a… Continue reading I’m an Analyst and the software engineers made fun of my code!
Inspired by Vicki I decided to build a Tweetbot – the code is available here. You can follow the tweetbot online – the architecture that Vicki proposed is basically what I did, only I made a few changes in the code. Time taken It’s worth pointing out first that it took me approximately 32 hours of… Continue reading How to use AWS Lambda to build a tweetbot
It gives me great pleasure to interview Vicki Boykis – we’ve chatted a lot on Twitter over the past few years and her blog/ side projects have been inspiring for my own. Vicki is a Data Scientist and Engineer who tweets awesome stuff. She’s well worth following. Her twitter bio – Born: Jewish in Russia. Raised:… Continue reading Interview with a Data Scientist – Vicky Boykis
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
I interviewed the interesting and fascinating Ian Wong – he’s the technical co-founder of OpenDoor, which I personally think is amazing as a concept! 1. What project have you worked on do you wish you could go back to, and do better? Pretty much any project I’ve worked on in the past Two projects stick… Continue reading Interview with a Data Scientist – Ian Wong of OpenDoor
I’m delighted to feature my friend Mick Cooney here as an interviewee. Mick has many years of experience in Finance and more recently in Insurance, he co-ran the Dublin R meetup which was very successful and helped foster a data science community in Dublin. More recently he’s been working over in London at an Actuarial… Continue reading Interview with a Data Scientist: Mick Cooney
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’ve been in the Data Science space for a number of years now, I first got interested in AI/Machine Learning in 2009 and have a background typical of a number of people in my field – I come from Physics and Mathematics. One trend I’ve run into both at Corporates and Startups is that there… Continue reading Building Full-Stack Vertical Data Products