Day-03 Unsupervised Learning

What is unsupervised learning ?

Unsupervised learning in artificial intelligence is a type of machine learning that learns from data without human supervision.

Unlike supervised learning, unsupervised machine learning models are given unlabeled data and allowed to discover patterns and insights without any explicit guidance or instruction.

Unsupervised learning uses self-learning algorithms—they learn without any labels or prior training.

Unsupervised learning algorithms are better suited for more complex processing tasks, such as organizing large datasets into clusters.

For example : Imagine that you have a large dataset about weather. An unsupervised learning algorithm will go through the data and identify patterns in the data points. For instance, it might group data by temperature or similar weather patterns

While the algorithm itself does not understand these patterns based on any previous information you provided, you can then go through the data groupings and attempt to classify them based on your understanding of the dataset. For instance, you might recognize that the different temperature groups represent all four seasons or that the weather patterns are separated into different types of weather, such as rain, sleet, or snow.

Points to Remember:

• Unsupervised learning uses self learning algorithms.

• Raw data is given to unsupervised model.

• Information based on similarities, difference and data patterns.