← Library · Core concept
Probabilistic Machine Learning
Probabilistic machine learning focuses on explicitly modeling uncertainty in data and predictions using the rules of probability. Instead of just giving a single answer, these models provide a distribution of possible answers, showing how confident they are in each. This approach is fundamental for tasks requiring risk assessment or where data is inherently noisy.
In plain terms
It's like a weather forecast predicting a 70% chance of rain, rather than just saying 'it will rain' or 'it will not rain.'
Why it matters
It allows models to quantify their uncertainty, which is crucial for decision-making in high-stakes applications.
Learn one new AI thing every day.
Daily Deck sends you seven plain-English cards like this every morning. Free.
Start free