Loss Functions & Optimization Explained Intuitively | How ML Models Learn

In this video, we break down Loss Functions and Optimization using simple, intuitive explanations—no heavy math required. You’ll learn how machine learning models measure their mistakes using loss functions and how optimization techniques like gradient descent help models learn and improve over time. We’ll cover: What loss functions are and why they matter Common loss functions like MSE, MAE, and Cross-Entropy How optimization works in practice Gradient descent intuition with real-world analogies Why learning rate plays a critical role in training This video is perfect for AI beginners, ML engineers, and developers who want a strong conceptual foundation before diving deeper into algorithms and frameworks.