Welcome to Imarticus Learning!br K-Nearest Neighbors (KNN) and Support Vector Machine (SVM) are two of the most important and widely used algorithms in Machine Learning. In this video, we break down how these models work, how they differ, and when to use them based on your data and specific use case.br br 🎯 Why Watch This Video?br Whether you’re just starting your ML journey or looking to deepen your understanding, this session simplifies complex algorithms into clear, real-world applications that you can instantly connect with.br br 📌 What You’ll Learn:br br 💡 K-Nearest Neighbors (KNN): A simple yet powerful “lazy learning” algorithm that makes predictions based on proximity.br 📊 Support Vector Machine (SVM): Learn about hyperplanes, margins, and how SVMs classify both linear and non-linear data.br 📈 KNN vs SVM: Discover which model performs better for different datasets and why.br 🧠 Real-World Use Cases & Metrics: Explore how these models are applied in industries, and learn to evaluate them using Accuracy, Precision, and Recall.br br 💼 Why Learn with Imarticus Learning?br br 📌 Expert Mentorship: Learn from professionals with years of real-world ML experience.br 📌 Flexible Learning: Structured, hybrid, and self-paced options designed for working professionals.br 📌 Comprehensive Support: Access mentorship, mock tests, and detailed study resources.br 📌 Career-Focused Outcomes: Our programs emphasize employability, with guaranteed placement support.br br 🚀 Master Machine Learning & Lead the Future of AI Innovation!br The Postgraduate Program in Data Science and Analytics (PGA) is a 6-month, 100 job-assured program for graduates and early professionals. Gain 300+ learning hours, 25+ hands-on projects, and expertise in 10+ tools including Python, Power BI, and Tableau.br br 💰 Highest Salary: 22.5 LPA | 52 Average Salary Hike | 2,000+ Hiring Partners.