Bias and Fairness

Bias in machine learning refers to the presence of systematic errors in a model's predictions due to underlying biases in the training data or algorithm. These biases can lead to unfair treatment of certain groups or individuals, perpetuating existing inequalities. It's crucial to identify and mitigate biases in your data and model to ensure fairness in your machine learning solution.