Introduction to Machine Learning in R
Who is this course for?
This course is aimed at anyone interested in applying machine learning methods to their data in order to: gain deeper insight, make better decisions or build data products
What will I learn?
"This course covers the fundamentals of machine learning and the methodology for applying these to real-world analytics problems. The course outlines the stages involved in a machine learning analysis, and walks through how to perform them using the R programming language and the tidymodels suite of packages. Participants will be provided with exercises to complete through the course in order to gain hands-on experience in using the methods presented.
The individual stages of: problem formulation, data preparation, feature engineering, model selection and model refinement will be walked through in detail giving participants a solid process to follow for any machine-learning analysis. This includes methods for evaluating machine-learning models in terms of a performance metric as well as assessing bias and variance. "
Skills tags:
- data
- machine learning
- R
- statistics