Machine learning is a branch of artificial intelligence that involves the development of algorithms and statistical models to enable computers to learn from and make predictions or decisions based on data. It encompasses various techniques such as supervised learning (e.g., logistic regression, decision trees, support vector machines), unsupervised learning (e.g., clustering, association), reinforcement learning, feature engineering, model evaluation, hyperparameter tuning, ensemble methods, dimensionality reduction, and semi-supervised learning. Machine learning algorithms aim to improve accuracy, precision, recall, F1 score, and other metrics through techniques like cross-validation, grid search, random search, and Bayesian optimization.
