Causal Inference and Discovery in Python: Unlock the secrets of modern causal machine learning with DoWhy, EconML, PyTorch and more

Author:   Aleksander Molak ,  Ajit Jaokar
Publisher:   Packt Publishing Limited
ISBN:  

9781804612989


Pages:   456
Publication Date:   31 May 2023
Format:   Paperback
Availability:   Available To Order   Availability explained
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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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Author:   Aleksander Molak ,  Ajit Jaokar
Publisher:   Packt Publishing Limited
Imprint:   Packt Publishing Limited
ISBN:  

9781804612989


ISBN 10:   1804612987
Pages:   456
Publication Date:   31 May 2023
Audience:   General/trade ,  General
Format:   Paperback
Publisher's Status:   Active
Availability:   Available To Order   Availability explained
We have confirmation that this item is in stock with the supplier. It will be ordered in for you and dispatched immediately.

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Aleksander Molak is a Machine Learning Researcher and Consultant who gained experience working with Fortune 100, Fortune 500, and Inc. 5000 companies across Europe, the USA, and Israel, designing and building 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, an innovative provider of AI and machine learning training for corporate teams, Aleksander is committed to empowering businesses to harness the full potential of cutting-edge technologies that allow them to stay ahead of the curve. Ajit Jaokar is a data scientist for Feynlabs, building AI prototypes for complex applications. He is also a course director for artificial intelligence at the University of Oxford. Besides this, Ajit is a visiting fellow in Engineering Sciences at the University of Oxford and conducts AI courses at the London School of Economics, Universidad Politécnica de Madrid, and the Harvard Kennedy School of Government as part of The Future Society. His work at Oxford and his company is based on interdisciplinary aspects of artificial intelligence, including AI with digital twins, quantum computing, metaverse, Agtech, and life sciences. His teaching is based on a methodology for AI and cyber-physical systems, which he is developing as part of his research.

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