Start Simple - The Power of Linear Models
Linear regression from scratch to Scikit-learn pipeline. Build the baseline every production team starts with.
Linear models1 power more production systems than most people realize: recommendation engines, fraud detection, pricing algorithms. The smartest ML teams start here, not because linear models are a stepping stone, but because they force you to understand your data and build something you can actually debug.
This tutorial takes the math you just learned (vectors, gradients, optimization) and turns it into a working prediction system.
Tutorial Goals
- Build linear regression from scratch with NumPy
- Understand why linear models dominate production systems
- Apply feature engineering to extend linear models
- Train and evaluate a housing price predictor with Scikit-learn
- Develop judgment for when simple beats complex
Why Start With Linear Models
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What you get
6 modules and 42 hands-on lessons with runnable code, failure diagnosis, and measured comparisons
2 capstone repositories you build, test, evaluate, and keep as portfolio proof
Videos, source code, complete projects and architecture diagrams
Recordings of live sessions
Discord community access
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