The AI technique that could imbue machines with the ability to reason by Karen Hao via @techreview

“At six months old, a baby won’t bat an eye if a toy truck drives off a platform and seems to hover in the air. But perform the same experiment a mere two to three months later, and she will instantly recognize that something is wrong. She has already learned the concept of gravity.” Yann LeCun, the chief AI scientist at Facebook, hypothesizes that a lot of what babies learn about the world is through observation. And that theory could have important implications for researchers hoping to advance the boundaries of AI.

I definitely agree with his observation on the number of pictures needed for learning to generally take place which makes it NOTHING like the way a baby or young child would learn things in real-life. So unsupervised learning it is then.

Small example of k-means in R:

km <- kmeans(iris[,1:4], 3)
plot(iris[,1], iris[,2], col=km$cluster)
points(km$centers[,c(1,2)], col=1:3, pch=8, cex=2)
table(km$cluster, iris$Species)

Automatically Segmenting Data With Clustering by @bilalmahmood via @kdnuggets

In this post, the author walks through one such algorithm called K-Means Clustering, how to measure its efficacy, and how to choose the sets of segments you generate.

Useful and worth reading even if you already know this just to make sure you are clear on it.