list the differences between supervised and unsupervised machine learning.

Supervised learning: Supervised learning is the learning of the model where with input variable ( say, x) and an output variable (say, Y) and an algorithm to map the input to the output.

That is, Y = f(X)

Unsupervised Learning: Unsupervised learning is where only the input data (say, X) is present and no corresponding output variable is there.

Here are the differences:

Criteria Supervised Learning Unsupervised Learning
Input Data Input data is labeled. Input data is unlabelled.
Data Set Uses training data set. Uses the input data set.
Use Use for prediction. Use for analysis.
Enables Enables classification & regression.

Enables Classification, Density Estimation, & Dimension Reduction