Data Science, Artificial Intelligence, Open Data, Machine Learning, Open Source.
scenarios where the model is likely to fail or make errors. The model can then be trained on both the original and synthetic data to evaluate its performance and identify potential weaknesses. This approach can help improve the model’s generalization and reduce overfitting, making it more robust to