Machine Learning with RReadDiscussCoursesPracticeImprove Article ImproveSave Article SaveLike Article LikeMachine Learning as the name suggests is the field of study that allows computers to learn and take decisions on their own i.e. without being explicitly programmed. These decisions are based on the available data that is available through experiences or instructions. It gives the computer that makes it more similar to humans: The ability to learn. Machine learning is actively being used today, perhaps in many more places than one would expect.This Machine Learning with R Programming tutorial aims to help learn both supervised and unsupervised machine learning algorithms with the help of well-explained and good examples.IntroductionAn Introduction to Machine LearningWhat is Machine Learning ?Getting Started with Machine LearningML – ApplicationsSetting up Environment for Machine Learning with R ProgrammingIntroduction to Machine Learning in RSupervised and Unsupervised Learning in R ProgrammingData Processing Introduction to Data in Machine LearningUnderstanding Data ProcessingData CleansingFeature ScalingSupervised Learning Regression Analysis in R ProgrammingLinear Regression Analysis in R Programming – lm() FunctionHow to Extract the Intercept from a Linear Regression Model in RPolynomial Regression in R ProgrammingLogistic Regression in R ProgrammingRegularization in R ProgrammingLasso Regression in R ProgrammingRidge Regression in R ProgrammingElastic Net Regression in R ProgrammingQuantile Regression in R ProgrammingNaive Bayes Classifier in R ProgrammingDecision Tree for Regression in R ProgrammingDecision Tree Classifiers in R ProgrammingConditional Inference Trees in R ProgrammingRandom Forest Approach in R ProgrammingRandom Forest Approach for Regression in R ProgrammingRandom Forest Approach for Classification in R ProgrammingRandom Forest with Parallel Computing in R ProgrammingRegression using k-Nearest Neighbors in R ProgrammingK-NN Classifier in R ProgrammingTesting Trained ModelsCross-Validation in R programmingK-fold Cross Validation in R ProgrammingRepeated K-fold Cross Validation in R ProgrammingLOOCV (Leave One Out Cross-Validation) in R ProgrammingThe Validation Set Approach in R ProgrammingUnsupervised LearningK-Means Clustering in R ProgrammingHierarchical Clustering in R ProgrammingHow to Perform Hierarchical Cluster Analysis using R Programming?DBScan Clustering in R ProgrammingLinear Discriminant Analysis in R ProgrammingAssociation Rule Mining in R ProgrammingApriori Algorithm in R ProgrammingTime Series AnalysisTime Series Analysis using ARIMA model in R ProgrammingExponential Smoothing in R ProgrammingTime Series Analysis using Facebook Prophet in R ProgrammingMiscKolmogorov-Smirnov Test in R ProgrammingMoore – Penrose Pseudoinverse in R ProgrammingSpearman Correlation Testing in R ProgrammingPoisson Functions in R ProgrammingFeature Engineering in R ProgrammingAdjusted Coefficient of Determination in R ProgrammingMann Whitney U Test in R ProgrammingBootstrap Confidence Interval with R ProgrammingApplications and ProjectsPredictive Analysis in R ProgrammingLast Updated : 28 Oct, 2021Like Article Save Article Please Login to comment...