Presented By
Prakhar Gupta
Founder of Adorithm | Measurement Expert | ML & AI Evangelist
Learn Why Do we need Causality in Data Science?
Tuesday, January 28 at 9 p.m. IST
This is a Webinar explaining why we need causal inference(Causality) in data science and machine learning. Causal inference brings a new fresh set of tools and perspectives that let us deal with old problems.
First off, designing and running experiments (typically with A/B testing) is always better than using causal inference techniques: you don’t need to model how data is generated. If you can do that, go for it!
There are Three Main Sources of influence in Casual inference: Computer Science, Statistics, and epidemiology and econometrics.
In this webinar, we will cover:
Presented By
Founder of Adorithm | Measurement Expert | ML & AI Evangelist