Machine Learning in R for Beginners: Super Simple Way to Start

Beginner's Guide to Machine Learning with R: Learn to install RStudio, handle data, and build models like linear regression and neural networks.

"R or Python? Which should you choose for data science and machine learning? Most people who work in these fields want to know the answer to this question.

Even if you choose Python, give R a chance. Let’s explore how R, with its powerful packages and IDEs, provides an excellent environment for machine learning, especially for beginners.

We’ll start with the basics and apply deep learning to dive deep into the ocean. So, let’s get started!

Getting Started with R

Before going into the Machine Learning with R, let’s first install RStudio.

You can download it from the CRAN (Comprehensive R Archive Network) there.

After installing R, you can download RStudio, IDE for R, which simplifies coding and includes various tools to help you visualize your data and output.

RStudio can be downloaded from here.

Basic R Syntax and Operations

R has unique syntax and operations. Let’s see a short overview.

• Variables and assignment: Use <- or = to assign values, - x <- 5
• Functions: Call functions using parentheses - sum(x, y)
• Data structures: Include vectors, lists, data frames, and matrices.
• Indexing: Access elements in data structures with brackets - vector[1] or dataframe$column.

Getting comfortable with these basics will give you a great start. These will help you read this one if you are a total stranger.

For more details on model building, missing value detection, data preparation, and many more, read the full article here.