April 2018
Intermediate to advanced
456 pages
11h 47m
English
We have discussed how to train our machines with past data on the basis of which they can learn, gain intelligence, and apply that intelligence on a new set of data. There are, however, situations when we do not have any prior knowledge of the data set we are working with, but we still want to discover interesting relationships among the attributes of the data or group the data in logical segments for easy analysis. The task of the machine is then to identify this knowledge without any prior training and that is the space of unsupervised learning. In this chapter, we will discuss how Clustering algorithms help in grouping data sets into logical segments and the association analysis ...