Supervised Learning
Supervised learning is a machine learning method where the model learns from labeled data, meaning each example used for training includes both inputs and desired outputs. By analyzing these input-output pairs, the algorithm iteratively improves its performance to make accurate predictions on unseen data. As part of artificial intelligence algorithms in the realm of technology and artificial intelligence, supervised learning plays a crucial role in various applications such as image classification, sentiment analysis, and speech recognition. This method sets the foundation for predictive models that can be fine-tuned with additional data to maintain their accuracy over time.