Day 23: Support Vector Machines (SVM) — Finding the Best Boundary

1. 1Explore the concept of Support Vector Machines (SVM) and its application in classification problems
2. 2Understand how SVM creates a decision boundary (hyperplane) to separate data into different categories
3. 3Apply SVM to a sample dataset to see how it finds the best possible boundary
4. 4Compare the performance of SVM with other classification algorithms
5. 5Implement SVM in a machine learning project to solve a real-world classification problem

Data scientists and machine learning engineers can benefit from understanding SVM to improve classification model performance and apply it to real-world problems

💡 SVM is a powerful supervised machine learning algorithm that finds the best possible boundary between classes, making it suitable for tasks where clear class separation is important

Learn about Support Vector Machines (SVM) and how it finds the best boundary for classification problems #MachineLearning #SVM