Sometime in 2019 after graduating I found myself in need of a job. I built a simple web scraping bot in a jupyter notebook over a weekend to help me find good roles quicker, and cut through some of the crud. To help with this, I made it parse through job descriptions and titles on Indeed, rank them according to the presence of certain keywords, and produce a condensed spreadsheet with any relevant information. Not too long after that I converted it into the simple webapp, hosted below.

No, not that posterior, this one: \(p(v|u)\). The probability of causes given outcomes. Finding such a probability, or even estimating it, lies at the crux of many learning algorithms. And one approach to finding such a posterior is via the use of generative models.