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`from causality import solution`
Recorded on Sep 04, 2023 in London, United Kingdom
A Python package that would allow us to address an arbitrary causal problem with a one-liner does not yet exist.
Fortunately, there are other ways to implement and deploy causal solutions at scale.
In this episode, Andrew shares his journey into causality and gives us a glimpse into the behind-the-scenes of his everyday work at causaLens.
We discuss new ideas that Andrew and his team use to enhance the capabilities of available open-source causal packages, how they strive to build and maintain a highly modularized and open platform.
Finally, we talk about the importance of team work and what Andrew's parents did to make him feel nurtured & supported.
Ready?
About The Guest
Andrew Lawrence is the Director of Research at causaLens (https://causalens.com/) Connect with Andrew:
- Andrew on LinkedIn: https://www.linkedin.com/in/andrew-r-lawrence/
About The Host
Aleksander (Alex) Molak is an independent ML researcher, educator, entrepreneur and a best-selling author in the area of causality.
Connect with Alex:
- Alex on the Internet: https://bit.ly/aleksander-molak
Links
- Code and Blogs
- DARA open-source framework (https://bit.ly/3Ql1VhF)
- causaLens GitHub (https://bit.ly/3QmoUJz)
- causaLens Blog (https://bit.ly/46TieJF)
- Videos
- Brady Neal Introduction to Causality
- Books
- Bishop (2006) - Pattern Recognition and Machine Learning
- Molak (2023) - Causal Inference and Discovery in Python
- Pearl & Mackenzie (2019) - The Book of Why
- Peters et al (2017) - Elements of Causal Inference
- Papers
- Full list of papers see here
Causal Bandits Podcast
Causal AI || Causal Machine Learning || Causal Inference & Discovery
Web: https://causalbanditspodcast.com
Connect on LinkedIn: https://www.linkedin.com/in/aleksandermolak/
Join Causal Python Weekly: https://causalpython.io
The Causal Book: https://amzn.to/3QhsRz4
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