Machinelearning
Machine learning is a branch of artificial intelligence focused on developing algorithms that improve their performance on tasks through experience with data. Rather than relying on explicit programming for every rule, machine learning systems learn patterns from examples and then apply them to new situations.
Machine learning encompasses several learning paradigms, including supervised learning, unsupervised learning, and reinforcement learning. Supervised learning
Common algorithms include linear and logistic regression, decision trees and random forests, support vector machines, and
A typical workflow involves collecting data, preprocessing and feature extraction, training a model, evaluating it on
Data quality, representation, and bias influence performance and fairness. Issues such as data leakage, overfitting, and
Applications span image and speech recognition, natural language processing, recommender systems, fraud detection, healthcare, finance, and