Glossary · Phase 3 · Machine learning
Unsupervised learning
Finding patterns, such as groups of similar customers, in data that has no right answers attached.
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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.
- model: The thing that learns: a formula with adjustable numbers that turns inputs into predictions.
- 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.
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