Welcome to the Unsupervised Learning community section! Here, you'll find curated resources to explore this fascinating field of machine learning.

📌 Getting Started

📚 1. Introduction to Unsupervised Learning

Unsupervised learning is a type of machine learning where the model learns patterns from unlabeled data. Key techniques include:

  • Clustering (e.g., K-means, DBSCAN)
  • Dimensionality Reduction (e.g., PCA, t-SNE)
  • Association Rule Learning (e.g., Apriori)
K-means Algorithm

🧪 2. Hands-on Examples

Try these beginner-friendly tutorials:

🚀 Advanced Topics

🔍 3. Deep Dive into Algorithms

Explore advanced methods like:

  • Hierarchical Clustering
  • Gaussian Mixture Models
  • Autoencoders
DBSCAN Clustering

📊 4. Data Visualization Tools

Use tools like Matplotlib, Seaborn, or Plotly to visualize results.

🌍 Real-World Applications

🧩 5. Case Studies

See how unsupervised learning is applied in:

  • Customer Segmentation
  • Anomaly Detection
  • Image Recognition
Dimensionality Reduction

📚 Expand Your Knowledge

Looking for more? Check out our Machine Learning Overview to understand the broader context!

Clustering Methods

All images and tutorials are designed to enhance your learning journey. Stay curious!