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
Category: machine learning
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
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. https://gist.github.com/springcoil/819937924cdbd7d648e8
Interview with a Data Scientist: Alice Zheng
I recently caught up with Alice Zheng a Director of Data Science at Dato – Alice is an expert on building scalable Machine Learning models and currently works for http://www.dato.com who are a company providing tooling to help you build scalable machine learning models easily. She is also a keen advocate of encouraging women in…… Continue reading Interview with a Data Scientist: Alice Zheng
