Use of machine learning is becoming ubiquitous and, even with a fancy name, it remains a tool in the statistical modeler belt. Every day, we leak billions of data from ourselves to companies ready to use it for their affair. Modeling through data get more common every day and mathematical model are the rulers of our life: they decide where we can work, if we can get a loan, how many years of jails we deserve, and more.

These days were a bit busy. I want to break the silence with an interesting link to a video. This is an interesting and fun to watch talk coming from the last PyCon. It talks about “practical statistics”, that is, how you can try to produce (or validate) a model when you can not compute the analytic model of a phenomenon. Many of the technique he describes can be used to any language, so it is suitable even if you do not program in Python. Anyway, look that, it is worth it. Moreover, this is just an excuse to suggest you to look around all the other videos from PyCon. They are well made and there are some interesting talk that should be watched.