Understanding Bayesian Inference
Bayesian inference is a fundamental method of statistical inference that involves using Bayes' theorem to update the probability estimate for a hypothesis as more evidence or information becomes available.
Key Concepts:
- Priors: Initial beliefs before new data.
- Likelihood: The compatibility of data with hypotheses.
- Posterior: Updated belief after considering new data.
Applications
Bayesian inference is used in various fields such as:
- Medical diagnostics 🩺
- Genetics 🧬
- Natural language processing 💬
- Machine learning 🤖
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