Unsupervised Learning Introduction

Welcome to the tutorial on Unsupervised Learning! This section will introduce you to the basics of unsupervised learning, a crucial component in the field of machine learning.

What is Unsupervised Learning?

Unsupervised learning is a type of machine learning where the algorithm learns from data that is not labeled or classified. Unlike supervised learning, where the input data is already tagged with the correct output, unsupervised learning focuses on finding patterns and relationships in the data without any guidance.

Key Applications

• Clustering: Grouping similar data points together.
• Association: Discovering interesting relationships between variables.
• Dimensionality Reduction: Reducing the number of variables in a dataset.

Types of Unsupervised Learning

1. Clustering: Algorithms like K-means, Hierarchical clustering, and DBSCAN.
2. Association: Algorithms like Apriori and FP-growth.
3. Dimensionality Reduction: Techniques like PCA and t-SNE.

Getting Started

To learn more about unsupervised learning, we recommend checking out our comprehensive tutorial on Clustering Algorithms.

Learn More

• Unsupervised Learning in Python
• Clustering Algorithms Explained

Machine Learning