You're reading from Causal Inference and Discovery in Python

Product typeBook

Published inMay 2023

PublisherPackt

ISBN-139781804612989

Edition1st Edition

Concepts

Data Science

Author (1)

Aleksander Molak

References

Abadie, A. (2021). Using Synthetic Controls: Feasibility, Data Requirements, and Methodological Aspects. Journal of Economic Literature, 59(2), 391-425.

Abadie, A., & Gardeazabal, J. (2003). The Economic Costs of Conflict: A Case Study of the Basque Country. Public Choice & Political Economy Journal.

Benjamens, S., Banning, L. B. D., van den Berg, T. A. J., & Pol, R. A. (2020). Gender Disparities in Authorships and Citations in Transplantation Research. Transplantation Direct, 6(11), e614.

Bradbury, J., Frostig, R., Hawkins, P., Johnson, M. J., Leary, C., Maclaurin, D., Necula, G., Paszke, A., VanderPlas, J., Wanderman-Milne, S., & Zhang, Q. (2018). JAX: composable transformations of Python+NumPy programs [Computer software]: http://github.com/google/jax

Brown, T., Mann, B., Ryder, N., Subbiah, M., Kaplan, J. D., Dhariwal, P., ... & Amodei, D. (2020). Language models are few-shot learners. Advances in Neural Information Processing Systems...

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Causal Inference and Discovery in Python

Published in: May 2023Publisher: PacktISBN-13: 9781804612989

Author (1)

Aleksander Molak

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.
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