Supervised learning is like having a helpful teacher who shows you how to turn messy information into clear insights. Let’s break it down:
Data Labeling: You begin with labeled data. This means you have pairs of information—like predicting how much a house will cost based on its features.
Model Training: Next, we use special tools, like linear regression or decision trees, to find patterns in the labeled data.
Predictions: After training, the model is ready to predict new information.
In short, supervised learning is all about learning from examples. It helps turn confusion into understanding!
Supervised learning is like having a helpful teacher who shows you how to turn messy information into clear insights. Let’s break it down:
Data Labeling: You begin with labeled data. This means you have pairs of information—like predicting how much a house will cost based on its features.
Model Training: Next, we use special tools, like linear regression or decision trees, to find patterns in the labeled data.
Predictions: After training, the model is ready to predict new information.
In short, supervised learning is all about learning from examples. It helps turn confusion into understanding!