What is the difference between supervised and unsupervised learning?
The main difference between supervised and unsupervised learning is the need for labeled training data.
Supervised learning
Uses labeled input and output data. The algorithm learns from the training dataset by making predictions and adjusting for the correct answer. The goal is to train the model to predict the output when given new data.
Unsupervised learning
Processes unlabelled or raw data. The algorithm explores patterns and predicts the output. There is no need to know or learn anything beforehand.
for more details:
Supervised vs. unsupervised learning: What’s the difference?
Difference between Supervised and Unsupervised Learning
Supervised vs Unsupervised Learning: Difference Between Them
Supervised and Unsupervised Learning in Machine Learning
Supervised vs. Unsupervised Learning
Supervised vs. Unsupervised Learning
