What is gradient boosting and how is it applied in predictive analytics? How does the model build sequential learners to improve prediction accuracy? What role do weak learners play in gradient boosting models? How does gradient boosting handle errors from previous models during training? What are the advantages and limitations of using gradient boosting in real-world predictive applications?