Master Causal Inference techniques and apply them effectively in the tech industry with this comprehensive guide. "Causal Inference in Python" by Matheus Facure provides practical insights and hands-on examples using Python to understand and implement causal inference methodologies. This book is ideal for data scientists, engineers, and researchers looking to move beyond correlation and understand true cause-and-effect relationships. Learn how to design experiments, analyze observational data, and build robust causal models to drive better decision-making in technological applications. Key Features: * Practical applications of causal inference in the tech industry. * Code examples and guidance using Python. * Covers fundamental concepts and advanced techniques. * Authored by Matheus Facure, an expert in the field. This paperback edition is perfect for anyone seeking to deepen their understanding of causal inference and its real-world impact. "Causal Inference in Python" is a valuable resource for professionals and students alike. Product Summary: Causal Inference in Python, Paperback, Matheus Facure, Tech Industry Applications, Data Science, Machine Learning, Python Programming, Causality.