The original definition given by Arthur Samuel in 1959: machine learning is a subfield of computer science that gives "computers the ability to learn without being explicitly programmed."  R is a free and open source statistical software package and is one of the most popular and power tools for handling machine learning problems.

This is the third workshop of "R Machine Learning" series. You'll learn about supervised learning tools, like bagging and random forest, and unsupervised learning tools, like hierarchical clustering. Time permitting, more supervised learning, like boosting will be covered. Knowledge about basics of R and linear regression is required for better understanding the contents of this workshop.

Here is the registration link.