Machine learning model explain

Linear regression is a statistical method used to model the relationship between a dependent variable and one or more independent variables. 

Logistic regression is a statistical method used for binary classification tasks, where the outcome variable has two possible classes 

Decision trees are a popular supervised learning method used for both classification and regression task


Random Forest is a powerful ensemble learning method based on decision tree.

a_ Bootstrapping: Random Forest starts by creating multiple bootstrap samples (random samples with replacement) from the original dataset 

Decision Trees Branch

K-means clustering is a popular unsupervised learning algorithm used for partitioning a dataset into K distinct, non-overlapping clusters.