Machine Learning Week 1: Unsupervised Learning

Today is the second day of my course Machine Learning by Stanford University on Coursera. It was an introduction to Unsupervised learning.

Unsupervised learning is the type of learning in which the machine is given a lot of data and the algorithm is told to automatically find the similar data among them and group them together based on structure/properties. The data given is totally unlabeled.

Clustering is a type of unsupervised learning. For example, grouping a similar stories on the internet or separating out the voices of two speakers from an audio.

To write prototypes on Machine Learning algorithm we can use programs like Octave or Matlab.

The link to Octave is here.

One clap, two clap, three clap, forty?

By clapping more or less, you can signal to us which stories really stand out.