Understanding Synthetic Data Generation and Its Implications

This chapter explores the nuances of synthetic data creation, emphasizing the need for models that accurately reflect real-world complexities. It highlights the significance of causal relationships and generalization in predictive modeling, showcasing the importance of well-founded mathematical principles.