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Artificial Intelligence Basics

Unsupervised Learning

Explore the methods and challenges of discovering patterns without labeled data.
Goal:
Learn how patterns are discovered without labels.
3Lessons
6Micro-lessons
IntermediateDifficulty
Lesson 1

Clustering Techniques

Understand different clustering methods and their applications.
Start2 Micro-lessons

Micro lesson 1
K-Means Clustering
Micro lesson 2
Hierarchical Clustering
Lesson 2

Dimensionality Reduction

Learn how to reduce data dimensions while preserving information.
Start2 Micro-lessons

Micro lesson 1
Principal Component Analysis (PCA)
Micro lesson 2
t-Distributed Stochastic Neighbor Embedding (t-SNE)
Lesson 3

Anomaly Detection

Identify unusual patterns that do not conform to expected behavior.
Start2 Micro-lessons

Micro lesson 1
Isolation Forest
Micro lesson 2
Local Outlier Factor (LOF)