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

Working in a major trend – Machine Learning

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

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

AI in the Enterprise (the problem)

I was recently chatting to a friend who works as a Data Science consultant in the London Area – and a topic dear to my heart came up. How to successfully do ‘AI’ (or Data Science) in the enterprise. Now I work for an Enterprise SaaS company in the recruitment space, so I’ve got a certain… Continue reading AI in the Enterprise (the problem)

A short email from Marvin Minsky – RIP

As a data scientist I regularly use results based upon the work of Marvin Minsky. This is an email exchange I had with him about 6 years ago, when I was working in Education and deciding to go back to school for Graduate School. On Mon, Jun 21, 2010 at 10:53 AM, Peadar Coyle <peadarcoyle@googlemail.com>… Continue reading A short email from Marvin Minsky – RIP

Interview with a Data Scientist: Nathalie Hockham

(Linkedin picture) I was very happy to interview Natalie about her data science stuff – as she gave a really cool Machine Learning focused talk at PyData in London this year, which was full of insights into the challenges of doing Machine Learning with Imbalanced data sets. Natalie leads the data team at GoCardless, a… Continue reading Interview with a Data Scientist: Nathalie Hockham

Interview with a Data Scientist: Thomas Wiecki

I interviewed Thomas Wiecki recently – Thomas is Data Science Lead at Quantopian Inc which is a crowd-sourced hedge fund and algotrading platform. Thomas is a cool guy and came to give a great talk in Luxembourg last year – which I found so fascinating that I decided to learn some PyMC3 🙂 1. What project have… Continue reading Interview with a Data Scientist: Thomas Wiecki

Interview with a Data Scientist (Hadley Wickham)

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.… Continue reading Interview with a Data Scientist (Hadley Wickham)

Interview with a Data Scientist: Trent McConaghy

At PyData in Berlin I chaired a panel – one of the guests was Trent McConaghy and so I reached out to him, to hear his views about analytics. I liked his views on shipping it, and the challenges he’s run into in his own world. 1. What project have you worked on do you… Continue reading Interview with a Data Scientist: Trent McConaghy

Information Retrieval

Attention conservation notice: 680 words about Information Retrieval, and highly unoriginal. The following is very much inspired by a course by Cosma Shalizi but I felt it was worth rewriting to get to grips with the concepts. This is the first of what is hopefully a series of posts on ‘Information Retrieval’, and applications of… Continue reading Information Retrieval