Changing the way you learn

Question	Answer
Support vector machine	Supervised learning models with associated learning algorithms that analyze data used for classification and regression analysis.
Random forests or random decision forests	an ensemble learning method for classification, regression, and other tasks, that operate by constructing a multitude of decision trees at training time and outputting the class that is the mode of the classes (classification) or mean prediction (regression) of the individual trees.
Gradient boosting	a machine learning technique for regression and classification problems, which produces a prediction model in the form of an ensemble of weak prediction models, typically decision trees.
k-means clustering	a method of vector quantization, originally from signal processing, that is popular for cluster analysis in data mining. k-means clustering aims to partition n observations into k clusters in which each observation belongs to the cluster with the nearest mean, serving as a prototype of the cluster.
Density-based spatial clustering of applications with noise (DBSCAN	It is a density-based clustering algorithm: given a set of points in some space, it groups together points that are closely packed together (points with many nearby neighbors), marking as outliers points that lie alone in low-density regions (whose nearest neighbors are too far away).

AI

	Created by Victor Vergara almost 6 years ago