Linear Regression It is used to estimate real values (cost of houses, number of calls, total sales etc.) based on continuous variable(s).

Logistic Regression Logistic Regression is used to estimate discrete values (usually binary values like 0/1) from a set of independent variables.

Decision Tree Decision Tree algorithm in machine learning is one of the most popular algorithm in use today; this is a supervised learning algorithm that is used for classifying problems.

Support Vector Machine (SVM) is a supervised learning algorithm and mostly used for classification tasks but it is also suitable for regression tasks.

Naive Bayes It is a supervised learning algorithm used for classification tasks. Hence, it is also called Naive Bayes Classifier.

K-Nearest Neighbors  (kNN) is a supervised learning algorithm that can be used to solve both classification and regression tasks.

Gradient Boosted Decision Trees (GBDT) GBDT is an ensemble algorithm which uses boosting method to combine individual decision trees.

K-Means Clustering Clustering is a way to group a set of data points in a way that similar data points are grouped together.

Random Forest It is a trademark term for an ensemble of decision trees. In Random Forest, we’ve collection of decision trees (so known as “Forest”).

Hierarchical Clustering It means creating a tree of clusters by iteratively grouping or separating data points.