Applied Machine Learning in R

Applied Machine Learning in R

What you’ll learn

• Understand the essential concepts related to machine learning
• Perform model cross-validation to assess model stability on independent data sets
• Execute advanced regression analysis techniques: best subset selection regression, penalized regression, PLS regression
• Perform logistic regression and discriminant analysis
• Apply complex classification techniques: naive Bayes, K nearest neighbor, support vector machine, decision trees
• Use neural networks to make predictions
• Use principal components analysis to detect patterns in variables
• Conduct cluster analysis to group observations into homogeneous classes