The idea behind this blog is to share the ideas and concepts that underpin the way I frame and solve problems as a working data scientist, from the theoretical concepts to their practical application.
Data science for me is very much a multidisciplinary field, as such I have found that time, and time gain, in order to solve real world problems I have to knit together concepts and theories from different STEM subjects to really understand a problem, and to have to weave together different technologies to really solve them.
As a consequence, the posts you’ll find here will cover a wide range of topics. Things like the math behind particular algorithms, Statistical Models, and ML models, why they work and when they won’t, data visualization, computational concepts, programming paradigms, useful programming libraries, tools, and frameworks, database systems, Thoughts around general workflows and methodologies in a professional context, how I weave these concepts together in practice. And my perspectives around what the future may hold for the field.