Big Data and Cloud Computing

In order to write a tutorial about classification, it was necessary to find an example that was broad enough that it would need to be sub-divided. Since I actually care about whether you remember this stuff, it needed to be something that a lot of people like and would relate to. And since I have a lot of international subscribers, it needed to be cross-cultural as well. So what is universal, cross-cultural, and dearly loved? Beer. There’s American beer, Mexican beer, German beer, Belgian beer….hell, even the Japanese make beer. There’s IPA, Lager, Pilsner. Dark, light, stout. There are so many ways to classify beer that we could spend weeks doing it (so naturally, I did). Now, before you can classify anything you have to determine the characteristics that you’re going to use. For beer you could use country of origin, color, alcohol content, type of hops, type of yeast, and calorie count among other things. That way you could sort based on any of those characteristics t...

n today’s world of big data and the internet of things, it is common for a business to find itself sitting atop a mountain of data. Possessing it is one thing, but leveraging it for data driven decision making is a much different ball game. Gut-feelings and institutionalized heuristics have traditionally been used to guide development of protocol and decision making, but the world of artificial intelligence and big disparate data is changing that. Everyone is trying to make sense of, and extract value from, their data. Those that are not will be left behind. This challenge (and opportunity) is not limited to certain industries. For instance, most companies are exploring how they can use data to make better marketing decisions, most retailers are using data to optimize their supply chains, and most manufacturers are using data for quality control of final products.  Almost all business problems (with surrounding data) can be broken down into two categories: supervised and unsu...