Let us learn about supervised and unsupervised learning.

Supervised Learning :

• Supervised learning is based on supervision.

• In supervising learning technique we train the machines using a labelled dataset and based on the training the machine predicts the output.

• The main goal of the supervise learning technique is to map the input variable with the output variable.

• Supervise machine learning categories are classification and regression.

• Examples of the supervised learning are Fraud detection, Spam filtering, Medical diagnosis, Speech, recognition, etc.

Unsupervised Learning :

• Unsupervised learning is not based on supervision.

• Unsupervised learning is machine training using unlabelled data set and the machine predict output without any supervision.

• The main goal of the unsupervised learning algorithm is to group the unsorted data according to the similar patterns and differences.

• Unsupervised learning are classified in clustering and Association types.

• Examples of unsupervised learning are Network analysis, Recommendation system, Anomaly detection, etc.