MACHINE LEARNING

Machine learning is a branch of artificial intelligence (AI) that enables computers to learn from data and improve their performance on specific tasks without being explicitly programmed. It involves the development of algorithms and models that can automatically discover patterns, make predictions, or generate insights from data. Machine learning techniques can be broadly categorized into supervised learning, unsupervised learning, and reinforcement learning, each suited for different types of tasks and data. Supervised learning involves training models on labeled data, where the correct answers are provided, to make predictions on new, unseen data. Unsupervised learning, on the other hand, involves training models on unlabelled data to uncover hidden patterns or structures within the data. Reinforcement learning focuses on training agents to interact with an environment and learn optimal behavior through trial and error. Machine learning finds applications across various domains, including healthcare, finance, marketing, and robotics, enabling automation, personalization, and decision-making based on data-driven insights. As technology advances and data availability increases, machine learning continues to play a crucial role in driving innovation and transforming industries worldwide.