Causal Analytics in Retail and Telco
Submitted by Gaurav Goswami (@gauravgoswami) on Friday, 28 April 2017
Section: Crisp talk for data engineering track Technical level: Intermediate
In this talk, I will discuss causal analytics using machine learning in the retail and telco domains. This talk should provide a brief overview of the value machine learning can provide in these domains along with the associated challenges and opportunities.
The key aspects of the talk are:
- Introduction to the need for causal analytics in retail and telco settings: identification and explanation of anomalies
- Discussion on the challenges and opportunities
- Using external data for additional signals in the retail setting
- Challenges in automating causal relationships only using observational data
- Overview of possible approaches and expected outcomes
I am currently working at IBM India as an Artificial Intelligence/Machine Learning expert. My Ph.D. thesis focuses on using machine learning and computer vision techniques to solve challenges in face recognition by improving the computation and combination of robust representations. I have had the opportunity to be a part of crafting a machine learning based solution for real world use cases in these domains. This talk will provide a brief overview of my experience and perspective on some of the key aspects of applied causal analytics.