What is machine learning, and why you should care (in 500 words)

It’s critical that you understand machine learning, even if just a little bit. Why? Machine learning is at the heart of the most common artificial intelligence systems today. It’s an important new technology that’s moved beyond hype to the brink of an exponential explosion, at the core of a 320% growth in AI-based startups last year. And, in combination with decision intelligence, Machine Learning has the potential to solve some of the most important problems faced by humanity today.

So here’s what you need to know.

Most importantly, machine learning is a way to build computer programs that learn from examples. Instead of writing software, machine learning experts “teach” the computer using tables of data showing what they want it to do. Usually, every row of the table contains two parts, which we could call the “gazintas” and the “gazoutas”. Gazintas might be a list of features of birds: 4″ bill, 10″ legs, brown head, 3″ toes, white eyes, and so forth. Gazoutas might be whether that bird eats fish or not: “yes” or “no” for each row of data.

For example:

Gazintas Gazouta
bill length leg length head color toe length eye color eats fish?
4 3 white 1.5 brown Y
2 1 green 4 red N
… (and so forth)

Now, here’s the best part:

The miracle of machine learning systems is that they allow computers to program themselves. Click To Tweet

You take this list of examples, give it to a learner, and it produces a learned system, which detects which aspects of a bird are most likely to go along with one that eats fish.  It works like this:

So, in our example, the learner might realize that if the legs are over a foot long, and the bill is over 3 inches long, the bird always eats fish.   It builds that into the learned system. Then, when you show it a new bird and say “does it eat fish?” it makes a pretty good guess.

That’s the essence of the idea. Everything else is detail and *tweaks on this core concept.  Seriously.

Here’s a great video by Sebastian Thrun and Katie Mallone that shows this “core” of machine learning in action.

Why is this amazing?

*with apologies to my machine learning friends, who know that the field is much bigger than what I cover here. But this is the most important part

**Image credit:http://micdotcom.tumblr.com/post/121589410557/add-learning-how-to-beat-super-mario-to-the-list

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