What are the main types of machine learning algorithms?

ML algorithms are broadly categorized by learning paradigm: Supervised Learning — trains on labeled data (linear/logistic regression, SVM, decision trees, neural networks); Unsupervised Learning — finds structure in unlabeled data (K-Means, PCA, DBSCAN, autoencoders); Semi-Supervised Learning — uses a small amount of labeled data with large amounts of unlabeled data; Reinforcement Learning — an agent learns by interacting with an environment and receiving reward signals (Q-learning, policy gradient methods); Self-Supervised Learning — labels are generated from the data itself (used in BERT, GPT pre-training).