What are Gaussian Mixture Models? | Soft clustering | Unsupervised Machine Learning | Data Science

📊 In this video, we introduce the concept of GMM using a simple visual example, making it easy for anyone to grasp. 💡

🧩 Ever wondered how data can belong to multiple groups simultaneously? That's where GMM comes in! We'll show you the difference between "hard clustering" (traditional clustering) and "soft clustering" (GMM's unique approach), helping you see how GMM can be more flexible in handling complex data distributions. 📈

🧮 And guess what? We won't overwhelm you with technical jargon! We'll keep it clear and straightforward, making GMM accessible to everyone.

🔍 But that's not all! We'll introduce you to the EM (Expectation-Maximization) algorithm, the secret sauce behind GMM. You'll see how EM plays a vital role in iteratively improving GMM's accuracy and how it all comes together to unlock hidden patterns in your data.

By the end of this video, you'll have a solid grasp of Gaussian Mixture Models, their applications, and how EM makes it all possible. 🤓

Happy Learning!