This Machine Learning with R dives into the basics of machine learning using an approachable, and well-known, programming language.
Look at real-life examples of Machine learning and how it affects society in ways you may not have guessed!
Explore many algorithms and models:
- Popular algorithms: Classification, Regression, Clustering, and Dimensional Reduction.
- Popular models: Train/Test Split, Root Mean Squared Error, and Random Forests.
R is a powerful language for data analysis, data visualization, machine learning and statistics. Originally developed for statistical programming, it is now one of the most popular languages in data science. You’ll be learning about the basics of R, and you’ll end with the confidence to start writing your own R scripts. But this isn’t your typical textbook introduction to R. You’re not just learning about R fundamentals, you’ll be using R to solve problems related to movies data. Using a concrete example makes the learning painless. You will learn about the fundamentals of R syntax, including assigning variables and doing simple operations with one of R’s most important data structures — vectors! From vectors, you’ll then learn about lists, matrix, arrays and data frames. Then you’ll jump into conditional statements, functions, classes and debugging. Once you’ve covered the basics – you’ll learn about reading and writing data in R, whether it’s a table format (CSV, Excel) or a text file (.txt). Finally, you’ll end with some important functions for character strings and dates in R.