Artificial Intelligence & Machine Learning
Supervised Learning
Definition
Supervised learning is a type of machine learning where the model is trained on a labeled dataset. This means that each piece of training data has a corresponding "correct" output or label.
Why It Matters
Supervised learning is the most common and well-understood type of machine learning. It is used for tasks where you have historical data and want to make predictions about the future.
Contextual Example
To train a model to identify pictures of cats, you would use supervised learning. You would feed it a large dataset of images, each labeled as either "cat" or "not a cat." The model learns the patterns associated with the "cat" label.
Common Misunderstandings
- Supervised learning problems are typically categorized as either "classification" (predicting a category, like "cat" or "dog") or "regression" (predicting a continuous value, like a house price).
- It requires a large amount of high-quality labeled data, which can be expensive and time-consuming to create.