What is Supervised Learning? Supervised learning is a type of machine learning where the model learns from labeled data, meaning it's given input-output pairs, and it learns to predict the output from the input.

Types:
1. Regression  i. Simple Linear Regression.
 ii. Multiple Linear Regression.
 iii. Polynomial Regression.
 iv. Support Vector Regression.
 v. Decision Tree Regression.
 vi. Random Forest Regression.

2. Classification  i. Logistic Regression.
 ii. Random Forest Classifier.
 iii. K-nearest Neighbor.
 iv. Support Vector Classifier.
 v. Naive Bayes.

What is Unsupervised Learning? Discovering patterns in data without labeled examples, enabling the model to identify hidden structures autonomously.

Types:
1. Clustering i. KMeans Clustering
ii. Hierarchical Clustering.
iii. DBSCAN Clustering.

UseCase Basically we use when we want model to classify category in data.