· beginner
Machine Learning Basics
What it means to learn from data, why a model that scores well can still be useless, and how to read a result someone hands you without being misled by it.
Written in house, from the work rather than from a syllabus. Every example is one we would use ourselves, and every quiz question explains why its answer is right.
What you’ll learn
- Explain what a model learns and what it does not
- Describe features and labels for a real problem
- Explain overfitting and why a held out test set is not optional
- Tell regression and classification apart and pick the right one
- Read accuracy, precision and recall without being misled
- Name the reasons a good model fails in production
Before you start
- · No maths beyond averages and percentages
- · No coding required