Bias in AI refers to systematic errors or prejudices that can occur within AI systems due to biased training data, faulty algorithms, or human biases. Addressing bias in AI is crucial for ensuring fairness, inclusiveness, and ethical practices in AI applications.
Supervised Learning is a Machine Learning approach where models are trained using labelled data, with both input and output pairs. By learning from the…