Why Zalando’s tech radar sucks as a stack

I’ve been programming professionally for about 5 years now. So I don’t consider myself a brilliant expert. Never the less one thing I think that I’ve learned is that it isn’t about the ‘technical problems’ it’s about whether or not you solve a real-world or meaningful problem. Some people call these ‘business problems’ but they… Continue reading Why Zalando’s tech radar sucks as a stack

Avoiding being a ‘trophy’ data scientist

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

Interview with a Data Scientist – Ian Wong of OpenDoor

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

Interview with a Data Scientist: Mick Cooney

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

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)

Interview with a Data Scientist: Greg Linden

I caught up with Greg Linden via email recently Greg was one of the first people to work on data science in Industry – he invented the item-to-item collaborative filtering algorithm at Amazon.com in the late 90s. I’ll quote his bio from Linkedin: “Much of my past work was in artificial intelligence, personalization, recommendations, search,… Continue reading Interview with a Data Scientist: Greg Linden

What happens when you import modules in Python

  I’ve been using Python for a number of years now – but like most things I didn’t really understand this until I investigated it. Firstly let’s introduce what a module is, this is one of Python’s main abstraction layers, and probably the most natural one. Abstraction layers allow a programmer to separate code into parts… Continue reading What happens when you import modules in Python

Are RNN’s ready to replace journalists?

I recently was experimenting with RNN’s in Keras. I used the example and edited it slightly. This is what I got for Nietzsche – as you can see the answer above to my question is No. ——– diversity: 0.2 ——- Generating with seed: “iginal text, homo natura; to bring it ab” iginal text, homo natura;… Continue reading Are RNN’s ready to replace journalists?

3 tips for successful Data Science Projects

I’ve been doing Data Science projects, delivering software and doing Mathematical modelling for nearly 7 years (if you include grad school). I really don’t know everything, but these are a few things I’ve learned. Consider this like a ‘joel test‘ for Data Science. Use a reproducible framework like Cookiecutter Data Science. My workflow used to… Continue reading 3 tips for successful Data Science Projects