A powerful paradigm for ML systems
My workflow for blogging in org mode, with jekyll and org-export.
Is hypothesis testing built upon a house of lies? No, probably not. But still, read this article.
Part II of my guide to data science interviews, focusing on algorithms, data structures, and general programming knowledge and best practices.
Part I of my guide to data science interviews, focusing on statistics and experimental design.
A brief discussion of my latest paper, which benchmarks various metrics used to compare complex networks, also known as graphs.
What is the connection between data types and logical propositions? Surprisingly, it runs quite deep. This post explores and illuminates that link.
Explanation of, and code for, a small Python tool for sampling from arbitrary distributions.
A summary of a project of mine in which I build an algorithmic classifier that identifies the genre of a piece of music based directly on the waveform.