Deep Learning: Utilizes neural networks with multiple layers to analyze various forms of data, enhancing capabilities in image and speech recognition
Decision Trees: Employs a tree-like model of decisions and their possible consequences, widely used for classification and regression tasks
Reinforcement Learning: An area of machine learning focused on making sequences of decisions by agents in a defined environment to maximize the notion of cumulative reward
Support Vector Machines (SVM): Effective in high-dimensional spaces, SVMs are ideal for classification problems, particularly binary classification
Random Forests: An ensemble learning method for classification and regression that operates by constructing multiple decision trees at training