Unsupervised Learning
Unsupervised learning is a type of machine learning where the model learns from unlabeled data. This means that the model does not have any pre-existing knowledge about the data, and it must learn to identify patterns and structures on its own. Unsupervised learning is often used for tasks such as: Clustering : This is the task of grouping data points together based on their similarities. For example, you could use unsupervised learning to cluster customer data into different groups based on their purchasing habits. Dimensionality reduction : This is the task of reducing the number of features in a dataset while preserving as much information as possible. For example, you could use unsupervised learning to reduce the number of features in a medical image dataset without losing any important information. Anomaly detection: This is the task of identifying data points that are significantly different from the rest of the data. For example, you could use unsupervised learni...