Reinforcement learning (RL) is a type of machine learning where an agent learns to make decisions by interacting with its environment to maximize some notion of cumulative reward. Unlike supervised learning, where models learn from labeled data, reinforcement learning operates on a trial-and-error b
Machine learning (ML) and deep learning (DL) are two of the most prominent technologies in the field of artificial intelligence (AI), but they are not the same thing. While both involve teaching machines to learn from data, their approaches, structures, and capabilities differ significantly.
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Unsupervised learning is a type of machine learning where a model is trained on data without explicit labels or guidance. Unlike supervised learning, where the model learns from labeled data to predict specific outcomes, unsupervised learning works with datasets that lack predefined outputs. The goa
Supervised learning is a core concept in machine learning where models are trained on labeled data to make predictions or decisions. It is one of the most widely used forms of machine learning due to its simplicity and effectiveness in solving real-world problems. In supervised learning, a model is
Machine learning is a subset of artificial intelligence (AI) that allows systems to learn from data, identify patterns, and make decisions with minimal human intervention. Unlike traditional computer programs that rely on explicit instructions for every task, machine learning models improve over tim