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🔍 Support Vector Machine (SVM) with Gaussian RBF Kernel | Machine Learning Tutorial

In this video, we dive deep into Support Vector Machines (SVM) using the Gaussian Radial Basis Function (RBF) Kernel, one of the most powerful tools for non-linear classification in machine learning. You'll learn:

✅ What SVMs are and how they work
✅ The intuition behind the RBF (Radial Basis Function) Kernel
✅ How to handle non-linearly separable data
✅ Key parameters like C and gamma, and how they affect the model
✅ Practical examples and visualizations in Python

Whether you're a beginner or brushing up on your ML skills, this tutorial will help you understand how SVMs use kernel tricks to classify complex data.
📁 Code & Resources: [Link to GitHub or notebook]
📚 Recommended Reading: [Link to blog or paper, if any]

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