What packages are used for machine learning in R?

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caret—for various classification and regression algorithms.
e1071—for support vector machines (SVM), naive Bayes classifier, bagged clustering, fuzzy clustering, and k-nearest neighbors (KNN).
kernlab—provides kernel-based methods for classification, regression, and clustering algorithms.
randomForest—for random forest classification and regression algorithms.
xgboost—for gradient boosting, linear regression, and decision tree algorithms.
rpart—for recursive partitioning in classification, regression, and survival trees.
glmnet—for lasso and elastic-net regularization methods applied to linear regression, logistic regression, and multinomial regression algorithms.
nnet—for neural networks and multinomial log-linear algorithms.
tensorflow—the R interface to TensorFlow, for deep neural networks and numerical computation using data flow graphs.
Keras—the R interface to Keras, for deep neural networks.

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