Yapay Zeka Destekli Test Otomasyonunda Temel Metrikler: Entropi, Çapraz Entropi ve Perplexity

📰 Medium · Machine Learning

Learn how to measure uncertainty in AI using entropy, cross-entropy, and perplexity to improve test automation and machine learning model reliability

intermediate Published 12 Apr 2026

Action Steps

Calculate entropy to measure uncertainty in AI models
Use cross-entropy to evaluate model performance
Apply perplexity to measure model complexity
Analyze information gain to optimize model design
Integrate these metrics into test automation processes to improve reliability

Who Needs to Know This

Data scientists, machine learning engineers, and test automation specialists can benefit from understanding these concepts to improve model performance and reliability

Key Insight

💡 Entropy, cross-entropy, and perplexity are essential metrics for measuring uncertainty and reliability in AI models