Glossary · Phase 3 · Machine learning
Churn
Customers leaving: a customer who stops buying has churned. Predicting churn is the running example in Phase 3.
In ordinary programming, you write the rules. Say you run an online shop. You might write: "if a customer hasn't ordered in 90 days, flag them as at risk of leaving." Customer data goes in, and answers come out. A customer who stops buying has churned, and the loss of customers is called churn.
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.
- 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.
- unsupervised learning: Finding patterns, such as groups of similar customers, in data that has no right answers attached.
Never trained an AI?
Teach a small one to write, right in your browser. It takes about 20 seconds and needs no account.