Supervised Learning
Supervised learning is a type of machine learning where a computer model learns from labeled examples to make predictions. Imagine teaching a child by showing them pictures of cats and dogs, clearly labeling each as either "cat" or "dog." Over time, the child learns to recognize these animals. Similarly, in supervised learning, the model gets input data along with the correct answers. By analyzing this data, it learns patterns and can predict outcomes for new, unseen data. This approach is commonly used for tasks like image recognition, spam detection, and medical diagnosis.
Additional Insights
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Supervised learning is a type of machine learning where a computer is trained to make predictions or decisions based on examples provided by humans. In this process, the computer learns from a labeled dataset, meaning each example comes with the correct answer. For instance, if the task is to identify cats in photos, the computer would be shown many images labeled "cat" or "not cat." By analyzing these examples, the model learns patterns and can then predict correctly when presented with new, unlabeled images. This method is widely used in applications like email filtering, speech recognition, and image classification.