KNN & K-Means Clustering Explained | Supervised vs Unsupervised Machine Learning | Session 9

Welcome to Session 9 of our FREE $300 Data Science with Python Course

In this video, we dive into two powerful machine learning techniques:

K-Nearest Neighbors (KNN) – a simple yet effective supervised learning algorithm used for classification and regression.
K-Means Clustering – a widely used unsupervised learning algorithm for discovering hidden patterns and grouping data.

Code file: https://github.com/Sajid-hafeez/Data-...

🔹 What you’ll learn in this session:
✅ The difference between Supervised vs Unsupervised Learning
✅ How KNN works step by step with real examples
✅ K-Means clustering explained with Python implementation
✅ Choosing the right K value
✅ Understanding distance metrics (Euclidean, Manhattan, etc.)
✅ Practical applications of KNN and K-Means in real-world data science projects

📌 Course Structure (so far):

Session 1: Introduction to Data Science with Python
Session 2: Data Cleaning & Preprocessing
Session 3: Encoding & Scaling
Session 4: Data Visualization
Session 5: Multiple Linear Regression
Session 6: Logistic Regression
Session 7: Decision Trees
Session 8: Ensemble Methods
Session 9: KNN & K-Means Clustering (this video)

👉 This course is valued at $300 but offered completely FREE. Don’t forget to subscribe and follow the full playlist to continue your data science journey!

📧 Contact / 1-1 Mentorship:
Email: [email protected]