Overview
Bias and fairness in machine learning are important topics that affect how algorithms make decisions. Bias can lead to unfair treatment of certain groups, while fairness aims to ensure equal opportunities for everyone. Understanding these concepts helps us create better models that are ethical and just. This introduction will explore the types of bias, their impact, and ways to promote fairness in machine learning systems.
📚 Key Learning Objectives
- ✓ Define bias and fairness in machine learning.
- ✓ Identify different types of bias in algorithms.
- ✓ Explain the impact of bias on decision-making.
- ✓ Discuss methods to reduce bias in models.
- ✓ Evaluate fairness in machine learning applications.
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