Glossary

Ensemble Averaging is a potent method in machine learning, aimed at combining multiple predictive models to boost overall prediction accuracy and performance.

Error-Driven Learning is a machine learning strategy that refines neural network weights based on discrepancies between predicted and actual outputs. This enhances accuracy.

Understanding the ethical implications of artificial intelligence is key to ensuring fairness, privacy, and safety in a world increasingly dominated by AI. Considerations span from eliminating bias in AI decisions, to securing data and protecting human rights, to examining economic consequences of automation. It is vital for AI practitioners to be accountable and responsible.