I am tentatively scheduled to speak at the 2016 Better Software Conference, June 5-10, in Las Vegas. I’ve spoken many times at the BSC but not for the past couple of years because the logistics didn’t work out.
My talk will be “Data Science 101” where I’ll explain the relationships between data science, machine learning, artificial intelligence, and classical statistics.
There are no standard, universally agreed on definitions of these terms. In my mind, data science is a generic, high level term that refers to many things including classical statistics and machine learning. I think of classical statistics as finding summary information (averages), finding correlations (R statistic), and making inferences (t-test).
I think of machine learning as techniques that make predictions (neural networks) and finding relationships (k-means clustering). In most cases, classical statistics can be done by hand (in theory anyway but often not in practice) but machine learning techniques realistically require a computer program.
In addition to explaining what all these terms mean, I’ll attempt to explain their relationship to Big Data, enterprise IT, and general career trajectory.
The Better Software Conference is always held in June, in Las Vegas. Some of the hottest weather I’ve ever experienced has been at BCS events, with temperatures well over 105 degrees F. Ironically, at Vegas conferences, it’s often very cold inside the hotels and convention centers because of the air conditioning.