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Causal Inference and Discovery in Python: Unlock the secrets of modern causal machine learning with DoWhy, EconML, PyTorch and more - Softcover
Synopsis
Demystify causal inference and casual discovery by uncovering causal principles and merging them with powerful machine learning algorithms for observational and experimental data
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Key Features
- Examine Pearlian causal concepts such as structural causal models, interventions, counterfactuals, and more
- Discover modern causal inference techniques for average and heterogenous treatment effect estimation
- Explore and leverage traditional and modern causal discovery methods
Book Description
Causal methods present...
About the Author
Aleksander Molak is an independent machine learning researcher and consultant. Aleksander gained experience working with Fortune 100, Fortune 500, and Inc. 5000 companies across Europe, the USA, and Israel, helping them to build and design large-scale machine learning systems. On a mission to democratize causality for businesses and machine learning practitioners, Aleksander is a prolific writer, creator, and international speaker. As a co-founder of Lespire.io, an innovative...
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- PublisherPackt Publishing
- Publication date2023
- ISBN 10 1804612987
- ISBN 13 9781804612989
- BindingPaperback
- LanguageEnglish
- Number of pages456
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Causal Inference and Discovery in Python: Unlock the secrets of modern causal machine learning with DoWhy, EconML, PyTorch and more
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