Start Simple - The Power of Linear Models
Learn how and why to build strong, interpretable baselines: explore linear regression end-to-end, from feature scaling to evaluation, with hands-on notebooks and real data.
Ready to put all that math you just learned into action? Perfect - because this is where everything clicks into place. You've got the mathematical foundation down (vectors, matrices, gradients), and now we're going to build your first real machine learning model from scratch.
Here's something that might surprise you: after 10+ years in this field, I've seen linear models1 power everything from Netflix recommendations to fraud detection systems. While everyone gets excited about the latest deep learning breakthroughs, the smartest teams I know always start with linear models. Why? Because they teach you to think like a true ML engineer.
This tutorial is all about building that engineering mindset. We'll take the mathematical concepts you just mastered and turn them into a working prediction system. You'll see why "start simple" isn't just good advice - it's how you build bulletproof ML systems.
Tutorial Goals
- Apply your new math skills to build your first ML model from scratch
- Understand why linear models are secret weapons in production systems
- Master the feature engineering techniques that make linear models shine
- Build and evaluate a real housing price predictor using Scikit-learn
- Develop the engineering judgment to know when simple beats complex