This post is all about causality. In data science we are often concerned with simple correlations. As someone trained in econometrics, as any one can tell you, the key thing that you should be concerned with is causality. We are […]
As you may know from last week I have been thinking about stochastic differential equations (SDEs) recently. As such, one of the things that I wanted to do was to build some solvers for SDEs. One good reason for solving […]
Recently, I’ve been reading up on stochastic differential equations. I’ve had some ideas on some projects at my day job, and quickly realized that I would need to write down some evolving processes that were inherently stochastic, thus why I’ve […]
Learn to deal with strings in pandas.
Some thoughts on strategic thinking in the world of data science. Here are 3 questions to kickstart your strategic thinking.
So last week I wrote about using dynamic optimization to understand how we should optimally respond to the global covid-19 crisis. This week, I wanted to take a step back and talk about the python package that made that all […]
Last week, I mentioned that even with all of our social distancing efforts, here in the great state of Utah, we would still overwhelm the medical system. It was kind of a bleak grim reminder that we are dealing with […]
I was sitting here, at home, locked away, being socially distant, and I got to thinking, “What is the point?” So I started to read a bunch about the data, and the algorithms, and the point behind social distancing. I’ve […]
Over the past few months I’ve had a thought coalescing in my brain. It has been swirling around banging up against the inner portions of my skull. With each collision with my head, and with other ideas, and situations I […]
One thing that I have been thinking a lot about since I wrote my chapter on matrix factorization methods, and since I am currently writing a chapter on graph theory is on the idea of a recommendation engine. (If you […]