Causal Inference and Discovery in Python

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The book explores the integration of causal inference principles with advanced machine learning techniques, focusing on both observational and experimental data. It aims to clarify the complexities of causal discovery, providing readers with a comprehensive understanding of how to effectively apply these concepts in practical scenarios. By merging theoretical foundations with computational methods, the text serves as a valuable resource for researchers and practitioners seeking to enhance their analytical capabilities in causal analysis.