Causal Inference, Practical Applications and Frameworks

This session will present the use of Python and DoWhy framework, to determine the actual cause of events in the real world, and how to debunk incorrect beliefs in your data.

Moreover, this session presents how Causation can help Machine Learning models to conciliate predictive performance, interpretability, fairness, and ethics, with the use of Causal Inference.
Agenda:

• Correlation
• Causal Analysis
• Correlation x Causation
• Finding Causation
• Causal Inference
• DoWhy Python Library (Demo)
• Q & A
• References

Name: Marcelo Beckmann
Company: Deutsche Bank – Cloud & Innovation Network – TDI
Corporate Title: Vice President – Lead Data Scientist

Bio: Marcelo Beckmann has 34 years working with IT, 25 of them working with banking and Fintech companies, being the last six years at Deutsche Bank Dublin Datalab, researching AI solutions for application in finance and banking automation. Studying and working with Statistics and Data Science since 2008, he obtained a Master and Doctorate degrees with focus in Data Preparation methodologies and Natural Language Processing applied to Financial Markets.