Machine Learning (ML) - Page 2

Machine Learning (ML) is a subfield of artificial intelligence that focuses on the development of algorithms and statistical models that enable computers to perform specific tasks without explicit instructions. Instead, ML systems learn from and make predictions or decisions based on data. The core idea is to enable machines to identify patterns and extract insights from large datasets, thereby improving their performance on tasks through experience. ML encompasses various techniques, including supervised learning, unsupervised learning, and reinforcement learning, each suited for different types of problems. Supervised learning uses labeled data to train models, unsupervised learning identifies patterns in unlabeled data, and reinforcement learning is based on optimizing actions through trial and error. Overall, ML plays a crucial role in enabling computers to adapt and learn from new information, making it a key technology in various applications, such as natural language processing, computer vision, and predictive analytics.