Artificial intelligence methods

Artificial intelligence methods encompass a wide range of techniques designed to enable machines to mimic human-like decision-making, problem-solving, and learning. These methods include supervised and unsupervised learning, reinforcement learning, and deep learning, each serving different purposes. Supervised learning uses labeled data to train models, while unsupervised learning identifies patterns in unlabeled data. Reinforcement learning optimizes decision-making through trial and error, and deep learning leverages neural networks to analyze complex data like images or natural language. Together, these methods power applications such as recommendation systems, autonomous vehicles, and advanced diagnostics, revolutionizing industries worldwide.