Introduction to Machine Learning in R

Get started with Machine Learning

• What is Machine Learning?
• What are typical problems solved using ML?
• What are the different types of learning?

Machine Learning in R resources/background

• Explore R packages designed for Machine Learning
• Find out about framework packages such as {tidymodels}
• Brief introduction to deep learning and Kaggle competitions

Explore and prepare the data

• Load and prepare various datasets
• Define the problem

Design machine learning workflow

• Split datasets
• Introduction to regression and classification problems
• Specify a model and set its mode and arguments

Data Pre-process

• How to deal with categorical variables
• What to do when we have missing values

Machine Learning Algorithms

• What are sources of error
• Introduce the Decision Tree algorithm
• Introduce the Random Forest algorithm
• Introduce the Gradient Boosting algorithm

Resampling and Tuning

• What is cross-validation
• Perform hyper-parameter tuning

Regression and Clustering

• Solve a regression problem
• Carry out K-means clustering