It is common for today’s scientific and business industries to collect large amounts of data, and the ability to analyze the data and learn from it is critical to making informed decisions. Machine learning is a branch in computer science that studies the design of algorithms that can learn. R is one of the major languages for data science. It provides excellent visualization features, which is essential to explore the data before submitting it to any automated learning, as well as assessing the results of the learning algorithm.

Why R?

  1. R is free: Unlike other proprietary software packages that require expensive licenses, R is open source and you can always download it for free. No matter where you travel, you can have access to R on your computer.
  2. R gives you access to cutting-edge technology: Top researchers develop statistical learning methods in R, and new algorithms are constantly added to the list of packages you can download.
  3. R is a useful skill: Employers that value analytics recognize R as useful and important. If for no other reason, learning R is worthwhile to help boost your resume.

Some popular R packages/libraries are caret, ggplot2, mlbench, class, caTools, randomForest, impute, ranger, kernlab, class, glmnet, naivebayes, rpart, rpart.plot.

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