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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.