The Top 10 Machine Learning Algorithms You Should Be Aware Of

Machine learning is a branch of artificial intelligence that gives computers the ability to learn from their experiences and get better on their own. Linear regression, decision trees, random forest, support vector machines, K-nearest neighbors, naive Bayes, and K-means clustering are some of the most popular algorithms used in machine learning. Linear regression is used for predicting a continuous outcome based on one or more predictor variables. Decision trees are used for decision-making and are extensively used in classification and regression assignments. Random forest is an ensemble learning technique that combines several decision trees to increase robustness and accuracy. Support vector machines are used for regression and classification, especially in high-dimensional datasets. K-nearest neighbors is a straightforward yet powerful method for regression and classification. Naive Bayes is a probabilistic technique used for spam filtering and text classification. K-means clustering is an unsupervised learning approach used to group together similar data points.