Supervised and Unsupervised AI: A Comprehensive Guide- How AI Works? -Robots Talking EP 19

Supervised learning, a key AI method, trains models using labeled data to predict outcomes for new inputs, encompassing techniques like regression, classification, and deep learning with applications in image recognition and natural language processing but facing challenges in data labeling and overfitting. Conversely, unsupervised learning discovers hidden patterns in unlabeled data through techniques like clustering and dimensionality reduction, useful for tasks like customer segmentation and anomaly detection, though evaluation and interpretation can be complex. The text further explores hybrid approaches like semi-supervised and self-supervised learning that combine aspects of both, as well as reinforcement learning and future trends including few-shot learning and foundation models, highlighting the evolving landscape of AI learning paradigms.