Glossary · Phase 3 · Machine learning
Model
The thing that learns: a formula with adjustable numbers that turns inputs into predictions.
The rule it finds is called a model. A model is a function with some adjustable numbers inside it. Those numbers are its parameters. Think of them as dials, like the dial on an oven. Training means turning the dials until the model's answers match the known answers as closely as possible. Then you use the model on new customers, whose answers you don't know yet.
Try it now
Sorting these by what data you have is how you start most real projects.
Learn it properly
What machine learning is · Programs that learn rules from examples instead of being told them. About 20 minutes.
Other terms from the same lesson
- accuracy: The share of predictions that were right. Misleading when one answer is much more common than the others.
- churn: Customers leaving: a customer who stops buying has churned. Predicting churn is the running example in Phase 3.
- machine learning: Getting a computer to learn a pattern from examples instead of writing the rules by hand.
- reinforcement learning: Learning by trial and error from a reward signal, rather than from right answers.
- self-supervised learning: Learning from data that supplies its own answers, such as hiding the next word of a sentence and guessing it. It's how language models are pretrained.
- unsupervised learning: Finding patterns, such as groups of similar customers, in data that has no right answers attached.
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