Molak, Aleksander
Causal Inference and Discovery in Python: Unlock the secrets of modern causal machine learning with DoWhy, EconML, PyTorch and more
- ISBN 13:
- 9781804612989
- author:
- Molak, Aleksander
- format:
- Paperback
- publisher:
- Packt Publishing
- language:
- English
- Publication Year:
- 2023
- Pages:
- 456
- Dimensions:
- 23.5 x 19.1 x 2.3 centimetres (0
- Genre:
- Computers, Artificial Intelligence, Computers,
- Condition:
- New
- Availability:
- Item usually sent within 5 working days
Description
Unlock the Secrets of Modern Causal Machine Learning with Python. Causal Inference and Discovery in Python demystifies causal inference and causal discovery by uncovering causal principles and merging them with powerful machine learning algorithms for observational and experimental data. You'll learn how to examine Pearlian causal concepts, such as structural causal models, interventions, counterfactuals, and more, and discover modern causal inference techniques for average and heterogeneous treatment effect estimation. With this book, you'll gain a comprehensive understanding of the Python causal ecosystem and harness the power of cutting-edge algorithms. You'll explore how "causes leave traces" and compare the main families of causal discovery algorithms. The final chapter provides a broad outlook into the future of causal AI, examining challenges and opportunities and offering a list of resources to learn more. A free PDF eBook is included with your purchase.
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