Machine learning is a branch in computer science that studies the design of algorithms that can learn. Typical machine learning tasks are concept learning, function learning or “predictive modeling”, clustering and finding predictive patterns. These tasks are learned through available data that were observed through experiences or instructions for example.
Machine learning hopes that including the experience into its tasks will eventually improve the learning. The ultimate goal is to improve the learning in such a way that it becomes automatic, so that humans like ourselves don’t need to interfere any more.
R provides a scripting language with an odd syntax. There are also hundreds of packages and thousands of functions to choose from, providing multiple ways to do each task. It can feel overwhelming.
The best way to get started using R for machine learning is to complete a project.
It will force you to install and start R (at the very least).
It will given you a bird’s eye view of how to step through a small project.
It will give you confidence, maybe to go on to your own small projects.