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!
I’ve been thinking and discussing with various people lately – ‘career path for data science’. Someone said to me recently: Go become a research scientist and specialise in specific machine learning models say NLP at a specific company such as Google, Amazon, etc. Become a data scientist at a startup or growth company and accept… Continue reading Adding value as Data Scientists
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
Source I’ve worked on Data Science projects and delivered Machine Learning models both in production code and more research type work at a few companies now. Some of these companies were around the Seed stage/ Series A stage and some are established companies listed on stock exchanges. The aim of this article is to simply… Continue reading How do we deliver Data Science in the Enterprise
I was recently speaking to some data science friends on Slack, and we were discussing projects and war stories. Something that came across was that ‘data science’ projects aren’t always successful. Somewhere around this discussion a lightbulb went off in my head about some of the problems we have with embarking on data science projects.… Continue reading One weird tip to improve the success of Data Science projects
Recently I’ve been speaking to a number of data scientists about the challenges of adding value to companies. This isn’t an argument that data science doesn’t have positive ROI, but that there needs to be an understanding of the ‘team sport’ and organisational maturity to take advantage of these skills. The biggest anti-pattern I’ve experienced… Continue reading Avoiding being a ‘trophy’ data scientist
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