Linear Regression Explained Simply | ML for Beginners

Linear Regression explained simply, from scratch, for complete beginners. No heavy math, no confusing jargon. In this video you will learn: • What Linear Regression is (with a real-life example) • What the "line of best fit" means • How the equation y = mx + b works, step by step • What error (loss) is and why we want it small • The simple idea behind Gradient Descent • A quick recap to lock it all in Key terms covered: feature (x), target (y), slope (m), intercept (b), error, loss, gradient descent. This is part of my Machine Learning playlist, where I teach ML from the basics. I'm a self-taught learner documenting my journey, so we are learning together. 🔔 Subscribe to Neurons ML for more beginner-friendly ML videos. 💬 Got a question or confused about something? Drop it in the comments and I'll reply. 🔗 GitHub: https://github.com/faiqcodes #LinearRegression #MachineLearning #MLForBeginners #DataScience #Python #NeuronsML