You have a problem that you think might need some Bayesian modelling A common question I’m asked is how do you start? In this tutorial I take you from a fresh data set, the data set is an educational dataset. I don’t know anything about the data, and I have no specific domain knowledge. I… Continue reading How to build a bayesian model in 30 minutes?
Category: machine learning
What is a Message Broker for?
I’ve been working in tech for a few years now, and that’s included writing a lot of code. One thing I never got my head around was what is a message broker? I’ve definitely seen them in architecture meetings, and heard people speak of ‘RabbitMQ’ and ‘Redis’ but I don’t really know what they’re for.… Continue reading What is a Message Broker for?
Why Probabilistic Programming is the next big thing in Data Science
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
What does it mean to be a Senior Data Scientist?
On being a Senior Data Scientist This post is partly for myself and based on various peoples conversations – it is also inspired by https://www.kitchensoap.com/2012/10/25/on-being-a-senior-engineer/ I’m trying to answer questions like ‘what do we expect from a Senior Data Scientist’. My job title is ‘Senior Data Scientist’ and I often joke I’ve no idea what… Continue reading What does it mean to be a Senior Data Scientist?
Avoiding the ML hipster trap
Machine Learning hipster effect Machine Learning is very in vogue at the moment. I feel that a pressure some junior data scientists and engineers feel is the need to do ML just to be a cool hipster, or as a friend of mine calls it ‘the ML hipster trap’. What is the ML hipster trap?… Continue reading Avoiding the ML hipster trap
How do we deliver Data Science in the Enterprise
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
One weird tip to improve the success of Data Science projects
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
Building Full-Stack Vertical Data Products
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
Three things I wish I knew earlier about Machine Learning
I’ve been working with Machine Learning models both in academic and industrial settings for a few years now. I’ve recently been watching the excellent Scalable ML from Mikio Braun, this is to learn some more about Scala and Spark. His video series talks about the practicalities of ‘big data’ and so made me think what I… Continue reading Three things I wish I knew earlier about Machine Learning
Probability Inequalities: Why should I care
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.